Underwater acoustic (UWA) communications are essential for high-speed marine data transmission but remain severely constrained by limited bandwidth, significant propagation loss, and sparse multipath structures. Conventional underwater acoustic multiple-input multiple-output (MIMO) systems primarily utilize spatial diversity but suffer from limited array resolution, causing angular ambiguity and insufficient spatial degrees of freedom (DoFs). This paper addresses these limitations through acoustic Reconfigurable Intelligent Surfaces (aRIS) to actively generate orthogonally distinguishable virtual paths, significantly enhancing spatial DoFs and channel capacity. An ocean-specific DoF-channel coupling model is established, explicitly deriving conditions for spatial rank enhancement. Subsequently, the optimal geometric locus, termed the Light-Point, is analytically identified, where deploying a single aRIS maximizes DoFs by introducing two and three additional resolvable paths in deep-sea and shallow-sea environments, respectively. Furthermore, an active simultaneous transmitting and reflecting (ASTAR) aRIS architecture with independent beam control and adaptive beam-tracking mechanism integrating unmanned underwater vehicles (UUVs) and acoustic intensity gradient sensing is proposed. Extensive simulations validate the proposed joint aRIS deployment and beamforming framework, demonstrating substantial UWA channel capacity improvements-up to 265% and 170% in shallow-sea and deep-sea scenarios, respectively.

Autonomous Underwater Vehicle (AUV) swarms face a fundamental synchronization challenge where millisecond-scale acoustic propagation delays prevent the nanosecond-level precision required for cooperative MIMO. We present a three-tier Multi-Agent Reinforcement Learning (MARL) framework using Magnetic Induction (MI) for ultra-precise synchronization within 100 m clusters while acoustic channels handle long-range data transmission. The key innovation lies in synergistic dual-modality operation: MI continuously provides nanosecond timing references as a deterministic control plane (8.5 ± 2.1 ns precision, 118× better than the 1 μs threshold), serving as the critical enabler that–combined with accurate channel estimation and positioning–enables acoustic C-MIMO beamforming gains previously unattainable underwater. Our hierarchical architecture employs the novel Delay-Sensitive Asynchronous Value Decomposition (DS-AVD) algorithm, explicitly handling 500 ms acoustic delays through temporal credit assignment and depth-dependent value decomposition. Comprehensive physics-informed simulations incorporating Bellhop acoustic models and hardware-validated MI measurements demonstrate: +12.3 dB beamforming gain, achieving 67% average array gain efficiency across 2-16 AUV configurations, 38.0±1.2 dB median Signal to Noise Ratio (SINR) (31% improvement), 140% range extension (2.1 km to 5.0 km), and 61% improvement of energy efficiency. DS-AVD achieves 95 ± 3% task success rate under nominal conditions (50 − 500 m depth) with graceful degradation to 82 ± 6% at 1000 m depth, where standard MARL approaches achieve only 11 ± 4%. Real-time feasibility is validated on embedded platforms with 47 ms inference latency and 2.3 W power consumption. This simulation-validated framework provides the foundation for next-generation underwater IoT systems that bridge the underwater-terrestrial performance gap.

Underwater wireless charging offers an effective solution to extend the operational time of autonomous underwater vehicles (AUVs). Both mobile and static wireless charging systems have been employed to support these operations. AUV swarms can significantly enhance the efficiency of remote underwater task execution. However, assigning tasks and planning recharging for AUV swarms in a distributed manner, especially under local communication constraints, presents a significant challenge. Unlike terrestrial environments, underwater wireless charging stations can only be deployed in specific locations. This paper introduces a model-based auction algorithm that jointly optimizes task assignment and AUV recharging schedules. The proposed algorithm intelligently plans recharging by accounting for factors such as the distance to charging stations and the queue length at charging stations. The developed solution is highly generic as it is independent of task location, task number, and task completion time which makes it adaptable to a wide range of operational scenarios.

This paper introduces a one-way ranging and time-alignment method for distributed multi-mode underwater communication networks that utilize both acoustic and optical front-ends. By capitalizing on the differences in propagation velocities between the optical and acoustic waveforms, the method enables precise distance and timing measurements between any two nodes by analyzing the time differences in signal arrivals. The theoretical foundation of the proposed technique is validated using the Cramer-Rao lower bound (CRLB), which serves as a performance benchmark. The method’s effectiveness is assessed through simulations and experimentally validated in a realistic underwater environment. The results demonstrate that the approach achieves excellent timing alignment with nanosecond precision and ranging accuracy at the centimeter level, utilizing only a single reference transmission. The results significantly enhance the reliability and efficiency of underwater communication systems, paving the way for advanced applications in marine exploration, environmental monitoring, and underwater robotics.

Video communication is the critical enabler of the metaverse and eXtended Reality (XR), where emerging technologies such as 360-degree videos, holograms, and point cloud videos impose substantial bandwidth demands. Although deep learning-based video compression and advanced codecs can significantly compress video data, Generative Artificial Intelligence (GAI) provides a new solution to generate videos under the supervision of minimal real-time streaming control data, thereby further reducing communication overhead. This paper proposes a video communication system using diffusion model-based GAI and topological data analysis. The GAI is used to generate videos using a limited number of video frames. Topological features extracted from video frames using topological data analysis are employed to ensure the quality of the generated video. This paper uses a mobile edge computing (MEC) system and presents its operational architecture. Experimental results on three different datasets demonstrate that the future frames generated at the edge server are of high quality compared to HEVC-encoded frames while also achieving significant compression. Furthermore, the proposed system maintains high fidelity in frames at the edge server, even under noisy conditions. Additionally, to validate real-world applicability, we implement a 5G testbed, where experimental results closely align with simulation outcomes, confirming the practicality and scalability of our approach.

Direct optical communication between underwater and aerial nodes such as drones offers a transformative approach for accessing underwater devices and sensors in shallow water environments. Unlike traditional underwater communication systems, which rely on buoys or surface vehicles to relay data between underwater devices and ground stations. Direct waterair optical communication enables greater operational flexibility and cost efficiency by utilizing drones to directly collect data or transmit commands. However, a significant challenge in implementing such systems is their limited reliability and short operational range, typically restricted to a few meters in both water and air. To address this limitation, this paper proposes and implements a LoRa-based modulation scheme for optical water-air communication using software-defined radio (SDR) technology. LoRa, a widely recognized radio frequency (RF) technology, is specifically designed for energy-efficient, low-rate communication, making it a promising candidate for enhancing the reliability of optical links. This paper presents a systematic approach to optimizing system parameters to improve link reliability across various scenarios. The experimental results demonstrate that the implementation of optical LoRa-based modulation offers a significant improvement in performance, achieving a gain of 7 dB to 15 dB compared to traditional Binary Phase Shift Keying (BPSK) modulation. This substantial gain underscores the effectiveness of LoRa-based modulation in enhancing the reliability and robustness of optical water-air communication links.

This paper presents a proof-of-concept for the UniSDM architecture, which is capable of simultaneously operating across acoustic, optical, magnetic induction, and RF communication modes. A flexible firmware stack is developed that integrates the logic for modem operation and supports multiple underwater communication modes mentioned above and the protocols and standards such as OFDM and JANUS for acoustics, as well as OFDM, single carrier, and IRDA-like protocols for optical communication. Additionally, it provides various interfaces, including a socket-based API, Ethernet tun-neling, and a graphical user interface (GUI). The firmware architecture incorporates cross-layer frame and waveform processing, enabling advanced communication paradigms such as multimode cooperative MIMO.

The demand for high-speed, long-range wireless communication systems has been steadily increasing, driven by the growing need for 6G and beyond networks in applications such as industry 4.0, Metaverse, holographic type communication, digital twins, etc. TeraHertz (THz) band communication has emerged as a promising solution to address these needs, offering ample bandwidth and high data rates. To extend the limited coverage and to ensure reliable and low-latency connectivity, this paper explores routing strategies for multi-hop outdoor communication within the THz band, taking into account the unique wireless channel effects associated with this frequency range, including significant path loss, interference, and scattering. A realistic channel model is developed using a hybrid modeling approach that incorporates both the randomness of the wireless channels, i.e., positions of scattering objects in the environment, and the fixed locations of terminals. By combining simulations with real-world measurement data, the performance of multihop THz communication is assessed in terms of connectivity, delay, and capacity. To overcome the limitations of THz band communication and enable longer transmission distances, innovative routing strategies are proposed for multi-hop communication. Global and local routing algorithms are proposed that jointly optimize routing based on end-to-end latency and path capacity, benchmarking them against standard methods such as the shortest path algorithm and local search techniques. Link delays and capacities are assessed using the established channel model, which is then integrated into the routing algorithms. Our approach significantly improves network performance by taking into account the unique characteristics of the THz band in outdoor applications, resulting in a 30% increase in path capacity and a 70% reduction in path delay compared to the local search method in the scenarios studied.

The growing prominence of eXtended Reality (XR), holographic-type communications, and metaverse demands truly immersive user experiences by using many sensory modalities, including sight, hearing, touch, smell, taste, etc. Additionally, the widespread deployment of sensors in areas such as agriculture, manufacturing, and smart homes is generating diverse sensory data. A new media format known as multisensory media (mulsemedia) has emerged, which incorporates many sensory modalities beyond the traditional visual and auditory media. 6 G wireless systems are envisioned to support the Internet of Senses, making it crucial to explore effective data fusion and communication strategies for mulsemedia. In this paper, we introduce a task-oriented multi-task mulsemedia communication system named MuSeCo, which is developed using unified Perceiver models and Conformal Prediction. This unified model can accept any sensory input and efficiently extract latent semantic features, making it adaptable for deployment across various Artificial Intelligence of Things (AIoT) devices. Conformal Prediction is employed for modality selection and combination, enhancing task accuracy while minimizing data communication overhead. The model is trained using six sensory modalities across four classification tasks. Simulations and experiments demonstrate that it can effectively fuse sensory modalities, significantly reduce end-to-end communication latency and energy consumption, and maintain high accuracy in communication-constrained systems.

Backscattering enables battery-less and perpetually operating Internet-of-Things (IoT) devices to sweep through ambient electromagnetic waves (in terrestrial networks) or acoustic waves (in underwater networks) rather than generate new waves. The emerging underwater acoustic backscatter communication (UABC) has the potential to avoid the need for underwater nodes to actively emit acoustic signals, thus, reducing their energy consumption. However, there is a lack of a clear design, comprehensive modelling or analysis of UABC systems. This paper studies a UABC system where a high-power transceiver transmits acoustic signals and a piezoelectric UABC node modulates and reflects the incident acoustic signals back to the transceiver. Specifically, a detailed new design for UABC nodes is proposed and a circuit model for the nodes is developed to analyze their acoustic impedance under different materials and operating frequencies. Based on the circuit model, a node load design is introduced to maximize the acoustic reflection coefficients; and a comprehensive communication analytical framework is established and is used to analyze how different UABC parameters, such as piezoelectric material properties, operating frequencies of UABC nodes, transmission distances, ambient noise intensities, carrier wave frequencies, and wind speeds, affect the bit error rate of UABC. Simulation results validate the effectiveness of the proposed designs and models as well as identify the key parameters influencing the UABC performance.

The common and well-accepted architectures for monitoring underwater (UW) environments involve UW drones for collecting information and fixed buoys to relay the information outside the water. Fixed buoys lead to some disadvantages, such as their high cost and limited coverage of UW devices. To address these problems, new architectures are considered in the literature, where the buoys are eliminated and instead aerial drones are used for collecting data from the UW ones. These architectures potentially lead to improved and more flexible UW monitoring and control. The existing literature for these novel architectures includes some channel models for optical wireless communication through the water-air (W-A) interface. The primary drawback of these models lies in the fusion of the received rays. Furthermore, the mathematical analysis is mostly carried out in 2D and then extended to 3D, leading to reduced modeling accuracy. In this paper, an accurate 3D ray-tracing solution is proposed for channel modeling and simulation of communication through W-A, where the rays observed at the receiver through multi-path are properly combined. Numerical analysis reveals insights and suggestions on optical channel gain variation over time, and also some conclusions on the overall communication system design, such as the best depth of UW devices and the best height of aerial drones.

Emerging from the symbiotic combination of nanotechnology and communications, the field of nanonetworking has come a long way since its inception more than fifteen years ago. Significant progress has been achieved in several key communication technologies as enablers of the paradigm, as well as in the multiple application areas that it opens. In this paper, the focus is placed on the electromagnetic nanonetworking paradigm, providing an overview of the advances made in wireless nanocommunication technology from microwave through terahertz to optical bands. The characteristics and potential of the compared technologies are then confronted with the requirements and challenges of the broad set of nanonetworking applications in the Internet of NanoThings (IoNT) and on-chip networks paradigms, including quantum computing applications for the first time. Finally, a selection of cross-cutting issues and possible directions for future work are given, aiming to guide researchers and practitioners towards the next generation of electromagnetic nanonetworks.

Nanotechnology is enabling the development of devices on a scale ranging from one to a few hundred nanometers. At this scale, a nanomachine is defined as the most basic functional unit, integrated by nano-components which can carry out sensing and actuation. Coordination and information communication among several nanomachines expand the potential applications of individual devices both in terms of complexity and range of operation. The resulting nanonetworks can cover wide areas, to reach unprecedented locations in a non-invasive way. Moreover, the integration of nanonetworks with classical networks and ultimately with the Internet results in a new networking paradigm, which is referred to as the Internet of Nano-Things (IoNT) by Akyildiz and Jornet one and a half decades ago.

Programmable metasurfaces constitute an emerging paradigm, envisaged to become a key enabling technology for Reconfigurable Intelligent Surfaces (RIS) due to their powerful control over electromagnetic waves. The HyperSurface (HSF) paradigm takes one step further by embedding a network of customized integrated circuit (IC) controllers within the device with the aim of adding intelligence, connectivity, and autonomy. However, little is known about the traffic that the network needs to support as the target electromagnetic function or boundary conditions change. In this paper, the framework of a methodology is introduced to characterize the workload of programmable metasurfaces which is then used to analyze the beam steering HSFs. The workload characterization leads to many useful insights into traffic behavior, including the spatio-temporal load incurred and the HSF limitations in terms of fine-grained tracking of moving targets. It is observed that the traffic is inherently bursty with an uneven spatial distribution of load and that finer resolution comes at the cost of an increased but less bursty load. An indoor mobility model indicates reasonable signaling load on the deployed surfaces. Finally, a statistical analysis on the traffic patterns is performed, showing that the incoming traffic can be well represented by an ON-OFF model.

The UnderWater Acoustic (UWA) communication is the foundation for oceanic information applications. However, existing UWA systems suffer from low data rate problem. Although the Multiple Input Multiple Output (MIMO) scheme is proved to be able to increase channel capacity in many terrestrial scenarios, the high cost and complexity of acoustic MIMO significantly limit its usage. Recently, the acoustic reconfigurable intelligent surfaces (acoustic RIS) concept has been proposed to address the aforementioned problem. In this paper, with the real-world constraints taken into consideration, three key components of the acoustic RIS are designed to realize the underwater RIS concept, including the new acoustic RIS hardware, the ultra-wideband (UWB) beamforming, and practical operation protocol. Specifically, a completely new hardware design of acoustic RIS is first provided, since existing electromagnetic RIS designed for terrestrial environments do not work for underwater acoustic waves. Then, the UWB beamforming solution is developed, since underwater acoustic RIS need to control the acoustic signals, whose bandwidth is comparable to its carrier frequency. Finally, the practical operation protocol is developed to realize the acoustic RIS functionalities in complex underwater environment. The acoustic RIS design is validated through both COMSOL multiphysics simulations and end-to-end Bellhop-based simulations.

In this paper, a Universal Underwater Software Defined Modem (UniSDM) architecture is proposed that may operate in different modes (acoustic, magnetic induction, optical and RF), in order to utilize the advantages of each mode and accordingly satisfy the requirements of many latest use cases in underwater communication systems. A detailed description of the novel UniSDM architecture is presented first. The novelty of this architecture is its flexibility, i.e., allowing the designers to produce a device that may include any type of modes operating seamlessly and jointly by exchanging data, control and synchronization. Many challenges, including high system costs and coordination between different modes, are addressed in the paper. Moreover, numerical evaluation is conducted to assess the performance of the proposed UniSDM architecture. Finally, the performance evaluation shows that the utilization of the UniSDM allows to decrease the transmission latency and improve the energy efficiency, while maintaining high reliability and robustness in underwater communication systems.

In recent years, many underwater communication applications have been proposed and tested, leading to the Internet of underwater things (IoUT) concept. In the IoUT, sensors may be deployed individually on sea surface and seabed as well as in water at different depths. They also may be integrated into underwater items such as fish, plants, autonomous underwater vehicles (AUVs), remotely operated underwater vehicles (ROVs), and divers. Depending on the application, different connectivity requirements must be satisfied such as data rate, latency, and reliability. However, the underwater communication channels pose a significant challenge to meet these requirements. To accommodate various applications with different service level agreements (SLAs), a multimode (acoustic, optical, and magnetic induction (MI)) communication system is proposed to take advantage of the modes' complementary features. Furthermore, an automatic network slicing (ANS) solution is proposed to provide globally optimized resource management, enhanced quality of service (QoS), simplified network operation, reduced deployment cost, and functional isolation of services. Taking the channel characteristics of the acoustic, optical, and MI communication modes into consideration, an optimization problem is formulated and solved for multimode IoUT (MM-IoUT) to enable admission control, routing, and dynamic resource allocation based on the different SLAs. Numerical analysis is conducted to verify the proposed solution and evaluate its performance.

Software-Defined Metasurfaces (SDMs) have ad-vanced from basic theoretical ideas to a key enabler for next generation wireless systems. When massively deployed in a wireless environment, they can realize precise, software-defined propagation of signals and wireless channel customizations. A plethora of studies have thoroughly investigated the physical design of the SDMs and their wireless channel engineering capa-bilities. This work introduces a novel architecture and associated processes for integrating SDMs into existing networked wireless systems. First, the integration architecture and the according complex underlying physics of the SDMs are presented. Then the software abstractions are proposed that enable the interaction of the surfaces in a physics-agnostic manner. These software abstractions require an SDM profile to operate in real-time, i.e., a database that accurately describes the capabilities of a given metasurface. Thus, the manufacturing time workflows are suggested to produce such a profile. The proposed solutions are evaluated in an actual physical setup/testbed.

Non-orthogonal multiple access (NOMA) is a well-accepted technology for future Wi-Fi systems to improve spectral efficiency. NOMA allows an access point (AP) to simultaneously serve multiple devices by splitting the transmit power between them. Using the superposition coding the AP combines signals of different frames with predefined power weights. However, as it is already known, the phase noise caused by hardware imperfections limits the performance of NOMA transmissions. The paper proposes a practical, easy-to-implement, and backward-compatible method to rotate the constellation of the low power signal in order to make it more robust to the phase noise. A mathematical model is developed to find such a rotation angle that minimizes the bit error rate (BER) of the low power frame. A new NOMA Wi-Fi prototype testbed is developed with the new feature of constellation rotation ability, which is used to validate the performance of our proposed method. Many experimental results show the proposed constellation rotation approach significantly decreases the BER in high signal-to-noise scenarios.

Programmable wireless environments (PWEs) utilize internetworked intelligent metasurfaces to transform wireless propagation into a software-controlled resource. In this article, the interplay is explored between the user devices, the metasurfaces, and the PWE control system from the theory to the end-to-end implementation. This article first discusses the metasurface hardware and software, covering the complete workflow from the user device initialization to its final service via the PWE. Furthermore, to be compatible with the 5G and 6G wireless systems, the software-defined networking (SDN) paradigm is extended to achieve scalable internetworking and central control in PWE deployments with multiple metasurfaces and multihop communication. Subsequently, the set of SDN foundations is exploited in order to abstract the physics behind PWEs and a theoretical framework is established to describe and manipulate them in an algorithmic form. This can lead to smart radio environments that are readily accessible from various engineering disciplines, facilitating their integration into existing networks, wireless systems, and applications. This article is concluded by outlining strategies for the optimal placement of metasurfaces within a PWE-controlled space, open challenges in PWE security, specialized SDN integration issues, and theoretical problems toward the graph-driven modeling of PWEs.

Terahertz (THz) band communications are envisioned as a key technology for 6G and Beyond. As a fundamental wireless infrastructure, THz communication can boost abundant promising applications. In 2014, our team published two comprehensive roadmaps for the development and progress of THz communication networks, which helped the research community to start research on this subject afterwards. The topic of THz communications became very important and appealing to the research community due to 6G wireless systems design and development in recent years. Many papers are getting published covering different aspects of wireless systems using the THz band. With this paper, our aim is looking back to the last decade and revisiting the old problems and pointing out what has been achieved in the research community so far. Furthermore, in this paper, open challenges and new research directions still to be investigated for the THz band communication systems are presented, by covering diverse topics ranging from devices, channel behavior, communication and networking, to physical testbeds and demonstration systems. The key aspects presented in this paper will enable THz communications as a pillar of 6G and Beyond wireless systems in the next decade.

To achieve higher throughputs in cellular networks, 3GPP proposes to use unlicensed frequency bands and develops technologies — the latest one is NR-U — allowing a cellular base station to transmit in unlicensed bands, which are already occupied by Wi-Fi networks. To enable fair channel sharing between two technologies, the base station uses a sort of CSMA/CA with binary exponential backoff similar to Wi-Fi. However, the base station can start data transmission only at strictly periodic time moments. Many papers propose sending a reservation signal between the end of the backoff procedure and such a moment to prevent nearby devices from accessing the channel. However, this approach significantly reduces Wi-Fi performance. The paper proposes a novel method CR-LBT of transmitting a reservation signal that greatly decreases channel resource waste caused by collisions and improves channel resource sharing fairness. With developed analytical models and simulations, it is shown that CR-LBT may simultaneously increase the throughput of both NR-U and Wi-Fi networks. The effect is more noticeable for the Wi-Fi network, the throughput of which may rise three times compared with the traditional method of sending the reservation signal. Finally, the influence of various factors on CR-LBT performance is studied.

The emergence of CubeSats as a viable means for realizing satellite networks at low costs has given rise to ubiquitous cyber-physical systems spanning air, ground, and space, in what is being recognized as the Internet of Space Things (IoST). IoST is expected to serve a wide variety of applications ranging from monitoring and reconnaissance to in-space backhauling, i.e., the network architecture must serve a plethora of application scenarios with differing service-level agreement (SLA) requirements over the same physical infrastructure in an end-to-end manner. At the same time, since the different use cases might belong to a variety of different stakeholders, IoST must support multi-tenancy and functional isolation of services. Consequently, a network slicing framework is vital to the success of IoST. To this end, an automatic network slicing framework for space-ground integrated networks is presented in this paper. The proposed framework has been designed to address the dual objectives of route computation and resource allocation with minimal SLA violations. Different from the existing state-of-the-art, the framework presented herein is purpose-built for ultra-dense CubeSat networks, and is fully automated. In other words, the framework is purely SLA-based, and does not require prior information concerning the resource requirements associated with a slice. Other key innovations introduced through this framework include a robust SLA model for slice customization, a novel topology construction mechanism, and a unique segment routing-based online admission control solution. Furthermore, the flexibility and efficacy of the proposed framework have been evaluated through a comprehensive use case driven evaluation scenario.

Intelligent surfaces at millimeter wave and terahertz band employ large antenna arrays based on advanced metamaterials to realize controllable wireless propagation. Such intelligent surfaces can achieve polarization tuning of electromagnetic waves, which allows polarization diversity under the ultra-massive MIMO communication, in addition to enhancing the beamforming gain and combating the transmission distance limitation. In this work, we analyze the dual-polarized intelligent surface channel and present an efficient precoding solution based on the array-of-subarray architecture that aims to maximize the spectral efficiency. Simulations are performed in comparison to conventional design based on single-polarized channel and obtained results demonstrate an increase in diversity gain with good spectral efficiency.

The emergence of CubeSats as a viable means for realizing satellite networks at low costs has given rise to ubiquitous cyber–physical systems spanning air, ground, and space, in what is being recognized as the Internet of Space Things (IoST). IoST is expected to serve a wide variety of applications ranging from monitoring and reconnaissance to in-space backhauling. The pervasiveness of cyber–physical systems of this kind necessitates a robust constellation design, characterized by optimized coverage and consistent connectivity. Thus, optimal constellation design is of great importance to system architects. However, the constellation design frameworks prevalent today do not scale well beyond a few dozen satellites, adversely impacting the system’s operational abilities. To this end, the objective of this article is two fold. The primary objective is the development of a modular and highly customizable large-scale constellation design framework, with the secondary objective involving the use of the proposed framework for designing robust constellations for IoST, serving a wide variety of use cases ranging from global coverage to region-specific coverage scenarios. More specifically, the framework presented herein has been developed to optimize constellation design based on CubeSat density, as well as a rigorous mathematical characterization of coverage and connectivity parameters. Furthermore, an extensive set of performance comparisons with existing state-of-the-art constellations has been presented to validate the efficacy of the IoST constellations designed using the proposed framework. Finally, the impact of design parameter variations on the developed constellations has also been examined in great detail.

Small satellites have shorter development cycles and lower costs than the traditional satellites in low-earth orbits (LEOs) and geostationary orbits (GEOs). These advantages and the ultra-wide spectrum availability in the Terahertz (THz) band enable profound potentials for inter-satellite links (ISLs) to achieve ultra-high throughput in both near-Earth and deep-space orbits. In this paper, the ISL channels at THz band are characterized and their link capacity is analyzed. First, the propagation channel effects in both Earth’s upper atmosphere and deep space are investigated to demonstrate the feasibility of THz band for ISLs. Second, an orbital perturbation model for satellite formation flying is proposed and analyzed with actual ephemeris information. Finally, a channel model is developed to investigate the diversity in both polarization and frequency domain for THz band inter-small-satellite communications. Our numerical results demonstrate that: 1) the ionospheric plasma does not affect the THz band signal propagation in near-Earth orbits; 2) the beam misalignment loss can be characterized by orbital perturbation factors; and 3) the ISLs in THz band can utilize the diversity techniques to achieve high throughput in both near-Earth and deep-space links.

Providing Ultra-Reliable Low-Latency Communications (URLLC) is one of the key challenges for 5G systems, which requires the redesign of both radio access technologies and the architectures. While 3GPP and the research community focus mainly on radio low layer functionality and architectural changes that enable URLLC, this article proposes a novel cross-layer framework that extends the already standardized 5G solutions to support a very massive number of users/flows in the system. The framework consists of a scheduler, a congestion avoidance algorithm, and a new traffic management algorithm, which together achieve the maximum capacity of 5G systems for URLLC, i.e., they maximize the load at which the reliability and latency requirements are satisfied for at least 99 percent of the users. Extensive performance evaluation results demonstrate that the proposed framework achieves the network capacity very close to the upper bound.

The increasing popularity of CubeSats has given rise to the possibility of ubiquitous cyber-physical systems serving a wide variety of applications that range from monitoring and reconnaissance to in-space backhauling. Expectedly, such systems are characterized by the need for a robust data routing framework that is purpose-built for resource-constrained CubeSats. To this end, a software-defined networking (SDN) based segment routing (SR) framework for CubeSats has been introduced in this paper. More specifically, a robust analytical characterization of the SR problem has been presented, along with an online algorithm for near-optimal route computation characterized by a provable performance bound. Furthermore, a comprehensive performance evaluation has also been provided, with the results obtained being benchmarked against classical SDN systems. The results demonstrate that the proposed framework not only ensures a higher level of demand satisfaction but also results in a significant reduction in control traffic, along with load balancing.

Programmable wireless environments (PWEs) utilize electromagnetic metasurfaces to transform wireless propagation into a software-controlled resource. In this work we study the effects of user device mobility on the efficiency of PWEs. An analytical model is proposed, which describes the potential misalignment between user-emitted waves and the active PWE configuration, and can constitute the basis for studying queuing problems in PWEs. Subsequently, a novel, beam steering approach is proposed which can effectively mitigate the misalignment effects. Ray-tracing-based simulations evaluate the proposed scheme.

Recent techniques utilizing reflectarrays or novel metamaterial-based surfaces to control wireless propagation environments have attracted great attention. While most solutions focus on sub-6 GHz wireless channel to assist in throughput enhancement, these intelligent surfaces have significant potentials in combating the transmission distance limitation and solving the non-line-of-sight transmission problems for the millimeter wave (30–300 GHz) and Terahertz-band (0.3–10 THz) where signal propagation is significantly attenuated in the atmosphere. The Ultra-Massive MIMO (UM MIMO) communication framework has been proposed in such frequency bands, which relies on the plasmonic antenna arrays to realize different operation modes, including anomalous reflection, transmission and reception, among others. In this paper, a joint beamforming scheme is developed based on fractional programming optimization to maximize the spectral efficiency under practical consideration of energy constraints of the UM MIMO communication platform. Numerical results are presented to show the performance comparison with existing solutions.

Intelligent surfaces exert deterministic control over the wireless propagation phenomenon, enabling novel capabilities in performance, security and wireless power transfer. Such surfaces come in the form of rectangular tiles that cascade to cover large surfaces such as walls, ceilings or building facades. Each tile is addressable and can receive software commands from a controller, manipulating an impinging electromagnetic wave upon it by customizing its reflection direction, focus, polarization and phase. A new problem arises concerning the orchestration of a set of tiles towards serving end-to-end communication objectives. Towards that end, we propose a novel intelligent surface networking algorithm based on interpretable neural networks. Tiles are mapped to neural network nodes and any tile line-of-sight connectivity is expressed as a neural network link. Tile wave manipulation functionalities are captured via geometric reflection with virtually rotatable tile surface norm, thus being able to tunable distribute power impinging upon a tile over the corresponding neural network links, with the corresponding power parts acting as the link weights. A feedforward/backpropagate process optimizes these weights to match ideal propagation outcomes (normalized network power outputs) to wireless user emissions (normalized network power inputs). An interpretation process translates these weights to the corresponding tile wave manipulation functionalities.

Programmable, intelligent surfaces can manipulate electromagnetic waves impinging upon them, producing arbitrarily shaped reflection, refraction and diffraction, to the benefit of wireless users. Moreover, in their recent form of HyperSurfaces, they have acquired inter-networking capabilities, enabling the Internet of Material Properties with immense potential in wireless communications. However, as with any system with inputs and outputs, accurate sensing of the impinging wave attributes is imperative for programming HyperSurfaces to obtain a required response. Related solutions include field nano-sensors embedded within HyperSurfaces to perform minute measurements over the area of the HyperSurface, as well as external sensing systems. The present work proposes a sensing system that can operate without such additional hardware. The novel scheme programs the HyperSurface to perform compressed sensing of the impinging wave via simple one-antenna power measurements. The HyperSurface can jointly be programmed for both wave sensing and wave manipulation duties at the same time. Evaluation via simulations validates the concept and highlight its promising potential.

Millimeter-wave (30-300 GHz) and Terahertz-band communications (0.3-10 THz) are envisioned as key wireless technologies to satisfy the demand for Terabit-per-second (Tbps) links in the 5G and beyond eras. The very large available bandwidth in this ultra-broadband frequency range comes at the cost of a very high propagation loss, which combined with the low power of mm-wave and THz-band transceivers limits the communication distance and data-rates. In this paper, the concept of intelligent communication environments enabled by Ultra-Massive MIMO platforms is proposed to increase the communication distance and data-rates at mm-wave and THz-band frequencies. An end-to-end physical model is developed by taking into account the capabilities of novel intelligent plasmonic antenna arrays which can operate in transmission, reception, reflection and waveguiding, as well as the peculiarities of the mm-wave and THz-band multi-path channel. Based on the developed model, extensive quantitative results for different scenarios are provided to illustrate the performance improvements in terms of both achievable distance and data-rate in Ultra-Massive MIMO environments.

The birth of wireless communication systems nearly 1 century ago has transformed and redefined the way humans communicate and interact. This transformation, which has opened boundaries between societies and eliminated cultural barriers, has evolved from the original paradigm of wireless electromagnetic communication systems. This paradigm has experienced numerous evolutionary developments that have not only brought along seamless connectivity for human interactions but also communication between machines and devices.

The papers in this special issue aims at capturing the most relevant theoretical foundations of molecular communications and networking (MCN) established so far, while giving a timely perspective on some emerging technological directions for engineering practical MCN applications. We believe these special issue papers can serve as an essential but complete handbook to approach MC as a research topic, as well as to start contributing to its timely and much needed technological evolution from theoretical exploration to practical implementation.

Over the past 10 years, molecular communication (MC) has established itself as a key transformative paradigm in communication theory. Inspired by chemical communications in biological systems, the focus of this discipline is on the modeling, characterization, and engineering of information transmission through molecule exchange, with immediate applications in biotechnology, medicine, ecology, and defense, among others. Despite a plethora of diverse contributions, which has been published on the subject by the research community, a general framework to study the performance of MC systems is currently missing. This paper aims at filling this gap by providing an analysis of the physical processes underlying MC, along with their information-theoretic underpinnings. In particular, a mathematical framework is proposed to define the main functional blocks in MC, supported by general models from chemical kinetics and statistical mechanics. In this framework, the Langevin equation is utilized as a unifying modeling tool for molecule propagation in MC systems, and as the core of a methodology to determine the information capacity. Diverse MC systems are classified on the basis of the processes underlying molecule propagation, and their contribution in the Langevin equation. The classifications and the systems under each category are as follows: random walk (calcium signaling, neuron communication, and bacterial quorum sensing), drifted random walk (cardiovascular system, microfluidic systems, and pheromone communication), and active transport (molecular motors and bacterial chemotaxis). For each of these categories, a general information capacity expression is derived under simplifying assumptions and subsequently discussed in light of the specific functional blocks of more complex MC systems. Finally, in light of the proposed framework, a roadmap is envisioned for the future of MC as a discipline.

The birth of wireless communication systems nearly a century ago has transformed and redefined the way humans communicate and interact. This transformation has evolved over many years and has brought along not only seamless connectivity for human interactions but also communication between machines and devices. While these communication systems are manmade artifacts, the research community has more recently turned its attention to other communication strategies that have spontaneously evolved in nature.

Programmable wireless environments enable the software-defined propagation of waves within them, yielding exceptional performance. Several building-block technologies have been implemented and evaluated at the physical layer in the past. The present work contributes a network-layer solution to configure such environments for multiple users and objectives, and for any underlying physical-layer technology. Supported objectives include any combination of Quality of Service and power transfer optimization, eavesdropping, and Doppler effect mitigation, in multi-cast or uni-cast settings. In addition, a graph-based model of programmable environments is proposed, which incorporates core physical observations and efficiently separates physical and networking concerns. The evaluation takes place in a specially developed simulation tool, and in a variety of environments, validating the model and reaching insights into the user capacity of programmable environments.

Inter-and intra-cell interferences significantly degrade the quality of service (QoS) in dense Wi-Fi networks. A promising way to cope with the interference is the use of centralized coordination of various stations in a Wi-Fi infrastructure network. Specifically, to avoid interference from the neighbors, the interfering stations need to execute orthogonal channel access and transmit data in non-overlapping channel times. The paper studies how to use the the features of IEEE 802.11aa/ax in order to guarantee reliable real-time video communication in dense Wi-Fi networks. In particular, IEEE 802.11aa allows an access point to reserve in advance a periodic sequence of channel times during which the data can be transmitted only between two devices, while the neighboring devices should keep silent. IEEE 802.11ax introduces trigger-based multi-user access, which can be done in a periodic way. To optimize and synchronize schedules of various access points a cloud controller can be used. Because of the random nature of the wireless channel and dynamic bit rate of a video stream, the amount of needed channel time varies. The paper proposes an approach on how to jointly use the reserved channel times and the idle channel times in order to satisfy QoS requirements of real-time video transmissions. A mathematical model is developed which can be used at the cloud controller to optimize the performance of the designed approach in terms of satisfying QoS requirements with the minimal channel time consumption. The high efficiency of the designed approach is evaluated with the real video traces.

Terahertz (THz)-band communication (0.1-10 THz) is envisioned as a key wireless technology to satisfy the in- creasing demand for faster data-rates in beyond 5G systems, thanks to its ultra-broad bandwidth. The very high path loss at THz frequencies and the limited transmission power of THz transceivers impose a major distance limitation for THz wireless communications. To increase the communication distance and the achievable data rates at THz-band frequencies, the concept of Ultra-Massive MIMO (UM-MIMO) has been introduced, which integrates a very large number of nano-antennas (e.g., 1024) in very small footprints (e.g., 1 mm^2). In this paper, an end-to-end model for UM-MIMO communication in the THz band is developed, by accounting for the properties of graphene- based plasmonic nano-antenna arrays and the peculiarities of three- dimensional THz propagation. The developed model is utilized to investigate the performance of the UM- MIMO channel. In particular, the path gain, the array factor and the the wideband capacity for both spatial multiplexing and beamforming regimes are analyzed. The results show that multi-Terabit-per-second links are feasible at distances of up to 20 m when utilizing 1024 × 1024 UM-MIMO systems at 0.3 THz and 1 THz.

Wireless communication environments are unaware of the ongoing data exchange efforts within them. Moreover, their effect on the communication quality is intractable in all but the simplest cases. The present work proposes a new paradigm, where indoor scattering becomes software-defined and, subsequently, optimizable across wide frequency ranges. Moreover, the controlled scattering can surpass natural behavior, exemplary overriding Snell's law, reflecting waves towards any custom angle (including negative ones). Thus, path loss and multi-path fading effects can be controlled and mitigated. The core technology of this new paradigm are metasurfaces, planar artificial structures whose effect on impinging electromagnetic waves is fully defined by their macro-structure. The present study contributes the software-programmable wireless environment model, consisting of several HyperSurface tiles controlled by a central, environment configuration server. HyperSurfaces are a novel class of metasurfaces whose structure and, hence, electromagnetic behavior can be altered and controlled via a software interface. Multiple networked tiles coat indoor objects, allowing fine-grained, customizable reflection, absorption or polarization overall. A central server calculates and deploys the optimal electromagnetic interaction per tile, to the benefit of communicating devices. Realistic simulations using full 3D ray-tracing demonstrate the groundbreaking potential of the proposed approach in 2.4GHz and 60GHz frequencies.

Underground communication systems present a variety of new research challenges. Here, the goal is to establish an efficient wireless connection between the transceivers in the challenging underground medium. Typical applications for this type of communication systems include soil condition monitoring, earthquake prediction, communication in mines/tunnels, etc. These applications require a gathering of relevant information from multiple locations, which suggests the use of multiple sensor nodes that would be organized in wireless underground sensor networks (WUSNs). Due to the harsh propagation conditions in the soil medium (including rock, sand, and water sheds), traditional wireless signal propagation techniques using electromagnetic waves can only be applied for very short transmission ranges. In recent years, magnetic induction (MI)-based transmission has been proposed to overcome these issues. In this approach, induction coils are utilized as antennas in the transceivers in order to reduce the vulnerability of signal propagation to the soil properties, in particular the soil conductivity. Correspondingly, the design rules for optimum MI-WUSNs have been shown to substantially differ from the design rules for the traditional wireless communication systems due to unique properties of the transmission channel. In this survey paper, the recent advances in the area of MI-WUSNs are discussed, which range from signal transmission techniques and network design to wireless power transfer and localization. Also, new research challenges in this area are provided.

This paper proposes an energy and spectrum efficient IoT network for 5G systems where spectrum is shared with the cellular system for spectrum efficiency and energy harvesting and energy transfer are utilized for energy efficiency. The IoT network, which consists of sensor nodes and a cluster head with a reliable energy source, reuses part of the cellular band whenever the cellular network does not utilize it. The cluster head performs spectrum sensing, random scheduling of the sensor nodes, and schedules some idle time for energy transfer. The sensor nodes harvest RF energy from the cellular traffic and the transferred energy from the cluster head. Provided the sensor nodes have sufficient energy, they transmit collected sensory data when scheduled. The inter-play between the cellular and IoT network introduces trade-offs between the spectrum availability, energy availability, information, and energy transfer. This paper shows that for the same cellular traffic level, as the number of sensor nodes in the network increases, the IoT network utilization increases resulting in a multi-user gain thanks to the broadcast nature of the energy transfer. The results offer insights into different operational regimes and exposes what type of IoT applications may be feasible with such networks.

Supporting on-line and adaptive traffic engineering in software-defined networks entails the fast, robust control message forwarding from software-defined switches to the controller(s). In-band control using the existing infrastructure is cost-efficient, but imposes a substantial barrier to timely transmissions of control messages. Also, due to the limited computational capability of a single controller, only the use of multiple controllers is practically viable for large-scaled networks. Therefore, in this paper, the optimal software-defined network planning is investigated with multi-controllers. First, the network planning problem is formulated as a nonlinear multi-objective optimization, which aims to simultaneously minimize the number of controllers and the control traffic delay for each switch. This planning problem is then partitioned into two sub-problems, i.e., multi-controller placement and control traffic balancing, which are respectively solved by the proposed fast-convergent algorithms. Furthermore, an adaptive feedback control mechanism is proposed to iteratively work out the two sub-problems and enable the dynamic network replanning, subject to the time-varying traffic volume and network topology. Simulations validate the adaptivity of our control scheme, which significantly reduces delay with maximum throughput for control flows, brings minimal impact to normal data flows, and requires the minimum controllers.

In-situ monitoring of oil reservoirs is crucial for determining the sweet spot of oil and natural gas reserves. Wireless sensor nodes are a promising technology to collect data from oil reservoirs in real time, such nodes are not sufficient for transmitting the required data within a power budget because of limitations caused by the very small size of sensors and the environment. To overcome limitations caused by harsh environmental conditions and power constraints, this paper proposes an accurate energy model framework of a linear oil sensor network topology that gives feasible sensors' transmission rates and sensor network topology while always guarantees enough energy. Since the magnetic induction communication channels is employed, we first examine the non-flat MI fading channels to obtain the accurate received signal qualities. Then, we design MI-based modulation and error control coding schemes and evaluate the energy consumption for MI transmissions to determine optimal sensors' transmissions rate and number of sensors while sensors' packet error rate and energy constraints are satisfied at the same time. we confirm the accuracy of our model via theoretical and simulation evaluations.

This paper proposes the Cella Ecosystem (CelEc) concept for emerging 5G ultra dense Networks, to evolve and supplement the Mobile Radio Network by using the crowd's User Equipments (UEs), densely distributed in our physical world and environment, as an integral part of the Infrastructure. Towards this end, CelEc establishes a decentralized ecosystem (the CelEc Tier) of numerous, unbound and ubiquitous networking and computing elements offering their networking functionalities and computing and storage resources to bridge coverage gaps, supplement capacity, increase data rates, and boost computing, whenever the Network is stressed. This is in the same spirit as the introduction of smaller sized cells throughout the evolution of mobile telephony, to maximize spectrum resource efficiency. Specifically CelEc, by enhancing the UEs with eNodeB's functionalities and additional networking operation functions, realises the smallest, portable, and reconfigurable cells (i.e., the Cella cells) allowing for dynamic massive deployment, and enables the efficient flows of data, whenever and wherever needed. As such CelEc provides for a dynamic reconfiguration of the Mobile Network infrastructure, in an effortless, costless (in terms of CAPEX) and flexible manner, hence removing the restrains of existing Small Cells beyond their static positioning. A preliminary evaluation of some of the ideas discussed in this paper for CelEc, showed among others, scalable massive mobile support, and significant improvements on the overall capacity, data rates, energy and spectral efficiency, as envisioned for 5G.

As a key enabling technology for 5G cellular systems, wireless virtualization allows multiple service providers to simultaneously and independently serve their users via virtualized network slices. However, differently from wired network virtualization that has been studied for many years, the research of wireless resource slicing is still at a very early stage. In this paper, based on the proposed 5G software-defined systems, novel wireless infrastructure-as-a-service (WIaaS) is introduced, which enables mobile virtual network operators to provide distinguished services to their subscribed users while sharing a common physical infrastructure. Specifically, through software-defined networking and fine-grained base station designs, a throughput-efficient resource allocation is proposed, by which, at the same time, (1) the data-rate requirements of traffic flows in virtual networks are fulfilled, (2) the isolation among applications and deployed protocols in networks is guarded, and (3) the global resource utilization is maximized. Simulations confirm that the proposed solution outperforms state-of-the-art schemes with greater system throughput and fairness support. Moreover, the performance improvement becomes significant when transmitted data has real-time requirements or the flow density and diversity are increased. Thus, WIaaS facilitates wireless resource slicing upon software-defined architectures and has opened a new research area of virtualization in next-generation cellular systems.

Wireless underground sensor networks (WUSNs) based on magnetic induction (MI) have been recently proposed as a promising candidate for underground networking. The benefit of the MI-WUSNs compared to other solutions (e.g. so-called Through-The-Earth communication) is related to the substantially lower path loss and lower vulnerability to the changes of the soil properties. In the past, some efforts have been made to characterize the signal transmission in MI-WUSNs. Those investigations, however, refer mostly to the information transmission. One of the target applications of the WUSNs is the object localization in the underground medium, which remains an open issue due to the complicated characteristics of the MI channels corrupted by the influence of soil. In this work, we propose a machine learning based solution for localization. In addition, a novel passive localization technique is introduced, which requires no signal from the target node and thus proves useful for rescue operations, where the battery of the node to be localized is either empty or damaged.

With the emergence of numerous novel dataintensive applications, the demand on fast wireless access is experiencing an unprecedented growth. Following this trend, the “Terabit era” is expected to become a reality in the near future. Terahertz technology is promising as an enabler due to its feature of an extremely high bandwidth. However, due to the high carrier frequency along with a high molecular absorption, the transmission distance is limited to a few meters only. In this work, the coverage problem and the achievable data rate performance of indoor THz wireless networks (THz-WNs) are investigated. In order to overcome the severe propagation loss and to improve the transmission range, a single frequency network (SFN) is advocated. The minimum individual user rate for different resource allocation schemes is analyzed, taking into account the effects of inter-symbol interference due to channel dispersion in the THz band and as a consequence of the SFN transmit protocol. Results demonstrate that the proposed SFN scheme is able to provide a high minimum achievable user data rate. The coverage probability increases from 25% when only a single access point (AP) is employed up to 95% when 20 APs are considered, for an output power of 1 W.

Millimeter-wave communication is one of the enabling technologies to meet high data-rate requirements of 5G wireless systems. Millimeter-wave systems due large available bandwidth enable gigabit-per-second data rates for line-of-sight (LOS) transmissions in short distances. However, for non-line-of-sight (NLOS) transmissions, millimeter-wave systems suffers performance degradation because the received signal strengths at user equipments (UEs) are not satisfactory. In this paper, the NLOS problem in millimeter-wave systems is treated from SoftAir (a wireless software-defined networking architecture) perspective. In particular, a so-called dynamic base station (BS) formation is introduced, which adaptively coordinates BSs and their multiple antennas to always satisfy UEs' quality-of-service (QoS) requirements in NLOS cases. First, the architecture for software-defined millimeter-wave system is introduced, where remote radio heads (RRHs) coordination is explained and millimeter-wave channel model between RRHs and UEs is analyzed. A ubiquitous millimeter-wave coverage problem is formulated, which jointly optimizes RRH-UE associations and beamforming weights of RRHs to maximize the UE sum-rate while guaranteeing QoS and system-level constraints. After proving the np-hardness of the coverage optimization problem with non-convex constraints, an iterative algorithm is developed for dynamic BS formation that achieves ubiquitous coverage with high data rates in LOS and NLOS cases. Through successive convex approximations, the proposed dynamic BS formation algorithm transforms the original mixed-integer nonlinear programming into a mixed-integer second-order cone programming, which is efficiently solved by convex tools. Simulations validate the efficacy of our solution that completely solves NLOS problem by facilitating ubiquitous coverage in 5G millimeter-wave systems.

Terahertz (0.06-10 THz) band serves as a promising technology to accommodate the exponential increase in data rates and number of connected devices. The THz band propagation is greatly affected by channel variations. In this paper, a novel and accurate approach is developed for time-varying channel modeling and tracking for the THz indoor communications. In particular, a three-dimensional time-varying THz channel model that captures the peculiarities in propagation parameters is presented. Moreover, based on the THz channel characteristics, an extended Kalman filtering approach is proposed to accurately track the line-of-sight component along time variation. Additionally, the proposed channel modeling and tracking approach under a realistic access-point-to-user-equipment link scenario in an office environment is evaluated in detail. Based on the simulation results validated from ray-tracing techniques, the proposed time-varying channel model yields satisfying system capacity.

This paper presents a time-varying channel model in three- dimensional environments for the 5G wireless system. Using the continuous-time Markov chain, the proposed model captures the statistical movement of the transceiver, the transition between line-of-sight and non-line-of-sight propagation scenarios, and the dynamic variation of propagation parameters. Moreover, a novel frequency- dependent factor that describes the dynamic path behavior is described in this model. According to the simulation results based on ray-tracing techniques and field measurements from the literature, the proposed time- varying channel model is validated at 5.2, 10, and 60 GHz. Furthermore, under realistic 5G device-to-device communication scenario, the simulation results and time- varying channel characteristics are highlighted, including the number of paths, path gain, delay spread, delay variation, Rician K-factor, and coherence bandwidth.

Wireless underground sensor networks enable many applications, such as mine and tunnel disaster prevention, oil upstream monitoring, earthquake prediction and landslide detection, and intelligent farming and irrigation among many others. Most applications are location-dependent, so they require precise sensor positions. However, classical localization solutions based on the propagation properties of electromagnetic waves do not function well in underground environments. This paper proposes a magnetic induction (MI)-based localization that accurately and efficiently locates randomly deployed sensors in underground environments by leveraging the multipath fading free nature of MI signals. Specifically, the MI-based localization framework is first proposed based on underground MI channel modeling with additive white Gaussian noise, the designated error function, and semidefinite programming relaxation. Next, this paper proposes a two-step positioning mechanism for obtaining fast and accurate localization results by: first, developing the fast-initial positioning through an alternating direction augmented Lagrangian method for rough sensor locations within a short processing time, and then proposing fine-grained positioning for performing powerful search for optimal location estimations via the conjugate gradient algorithm. Simulations confirm that our solution yields accurate sensor locations with both low and high noise and reveals the fundamental impact of underground environments on the localization performance.

Magnetic induction (MI)-based communication systems have gained increased attention in recent years. Typical applications for these systems lie in the area of wireless power transfer, near-field communication (NFC), and wireless sensor networks in challenging environments. In this paper, a system for simultaneous wireless information and power transfer (SWIPT) using MI-based signal transmission is designed for supporting one data stream and multiple parallel power streams. One of the possible applications for this scheme is an NFC-based access point. The overall system is optimized to guarantee a certain quality-of-service for the data stream as well as a maximum sum receive power for all power receivers (max-sum problem) or a maximum receive power for the worst power receiver (max-min problem), respectively. Both optimization problems turn out to be non-convex, such that the optimum solution cannot be found with limited computational complexity. Hence, we provide efficient suboptimal solutions. In this context, a convex approximation of the transmit power constraint in MI-based multiple-input multiple-output systems turns out to be very useful. A very high achievable power efficiency renders the proposed MI-based SWIPT system very promising.

Heavy-tailed (HT) traffic (e.g., the Internet and multimedia traffic) fundamentally challenges the validity of classic scheduling algorithms, designed under conventional light-tailed (LT) assumptions. To address such a challenge, this paper investigates the impact of HT traffic on delay-based maximum weight scheduling (DMWS) algorithms, which have been proven to be throughput-optimal with enhanced delay performance under the LT traffic assumption. First, it is proven that the DMWS policy is not throughput-optimal anymore in the presence of hybrid LT and HT traffic by inducing unbounded queuing delay for LT traffic. Then, to solve the unbounded delay problem, a delay-based maximum power-weight scheduling (DMPWS) policy is proposed that makes scheduling decisions based on queuing delay raised to a certain power. It is shown by the fluid model analysis that DMPWS is throughput-optimal with respect to moment stability by admitting the largest set of traffic rates supportable by the network, while guaranteeing bounded queuing delay for LT traffic. Moreover, a variant of the DMPWS algorithm, namely the IU-DMPWS policy, is proposed, which operates with infrequent queue state updates. It is also shown that compared with DMPWS, the IU-DMPWS policy preserves the throughput optimality with much less signaling overhead, thus expediting its practical implementation.

Body Area Sensor Networks (BASNs) are a challenging research area with applications in healthcare and entertainment. Due to the importance of the target applications in the daily life, BASNs are a promising candidate for being included into the future Internet of Things (IoT). In particular, the data gathering of the human activity may help customizing the services provided by the IoT and thus dramatically improve the IoT user experience. Magnetic Induction (MI) based communication is known in the context of wireless power transfer (WPT), near-field communication (NFC), and wireless sensor networks (WSNs) in challenging environments. In this approach, induction coils are utilized as antennas in the sensor nodes. Distributed beamforming is a well-known technique, that has been thoroughly investigated in the past. Here, the basic idea is to align the phases of signals from different sensor nodes in such a way that a virtual multiple-input multiple-output (MIMO) system with favorable properties is created. For example, this strategy may lead to an improved directionality of the transmitted signals and increase the achievable data rate. In this work, we analyze the potential of the distributed beamforming based MI-BASNs. We observe a significant increase of the achievable data rate for the proposed distributed beamforming compared to our selected baseline scheme.

Scheduling is one of the most important resource allocation for networked systems. Conventional scheduling policies are primarily developed under light-tailed (LT) traffic assumptions. However, recent empirical studies show that heavy-tailed (HT) traffic flows have emerged in a variety of networked systems, such as cellular networks, the Internet, and data centers. The highly bursty nature of HT traffic fundamentally challenges the applicability of the conventional scheduling policies. This paper aims to develop novel throughput-optimal scheduling algorithms under hybrid HT and LT traffic flows, where classic optimal policies (e.g., maximum-weight/backpressure schemes), developed under LT assumption, are not throughput-optimal anymore. To counter this problem, a delay-based maximum-weight scheduling policy with the last-in first-out (LIFO) service discipline, namely LIFO-DMWS, is proposed with the proved throughput optimality under hybrid HT and LT traffic. The throughput optimality of LIFO-DMWS gives that a networked system can support the largest set of incoming traffic flows, while guaranteeing bounded queueing delay to each queue, no matter the queue has HT or LT traffic arrival. Specifically, by exploiting asymptotic queueing analysis, LIFO-DMWS is proved to achieve throughout optimality without requiring any knowledge of traffic statistic information (e.g., the tailness or burstiness of traffic flows). Simulation results validate the derived theories and confirm that LIFO-DMWS achieves bounded delay for all flows under challenging HT environments.

Wireless underground sensor networks (WUSNs) present a variety of new research challenges. Magnetic induction (MI) based transmission has been proposed to overcome the very harsh propagation conditions in underground communications in recent years. In this approach, induction coils are utilized as antennas in the sensor nodes. This solution achieves larger transmission ranges compared to the traditional electromagnetic (EM) waves based approach. In the past, some efforts have been made to characterize the signal transmission in MI-WUSNs. Those investigations, however, refer mostly to the information transmission. One of the open issues, that may constrain the system design in some of the applications, is the powering of the individual sensor nodes. Due to the low accessibility of the nodes, a new method of wireless power transfer (WPT) for MI-WUSNs is proposed in this work. This method is mainly based on simultaneous signal transmissions from multiple sensor nodes with optimized signal constellations. Furthermore, the optimal scheduling for power transmission and reception is provided, which maximizes the energy efficiency of the network charging procedure. The proposed method is compared with the naive approach and shows a significant improvement of the system performance in terms of energy efficiency.

With the emergence of numerous novel data-intensive applications, the demand on fast wireless access for huge data file transfer and fast mobile data access is growing rapidly. Following this trend, the “Terabit era” is expected to become a reality in the near future. Terahertz (THz) technology is promising as an enabler due to its unique features, among others such as extremely high bandwidth, resistance to eavesdropping and minimal risk to human health. However, a number of technical hurdles need to be overcome to achieve such ultra-fast data rate of Terabit-per-second (Tbps) in the THz spectrum. In this work, a fundamental insight into the modulation scheme design is aimed to be established for THz communication systems. A strategy for transmission scheme selection and a corresponding efficient power allocation algorithm are proposed. Bounds on the maximum distance are determined for which data rates in the order of Tbps can be achieved. The results provide a fundamental insight into the selection of THz transmission schemes for given performance requirements.

Nanotechnology is enabling the development of miniature devices able to perform simple tasks at the nanoscale. The interconnection of such nano-devices with traditional wireless networks and ultimately the Internet enables a new networking paradigm known as the Internet of Nano-Things (IoNT). Despite their promising applications, nano-devices have constrained power, energy, and computation capabilities along with very limited memory on board, which may only be able to hold one packet at once and, thus, requires packets to be delivered before certain hard deadlines. Toward this goal, a fully-distributed computation-light provably-correct scheduling/MAC protocol is introduced for bufferless nano-devices, which can maximize the network throughput, while achieving perpetual operation. More specifically, the proposed scheduling algorithm allows every nano-device to make optimal transmission decisions locally based on its incoming traffic rate, virtual debts, and channel sensing results. It is proven that the proposed algorithm is timely throughput optimal in the sense that it can guarantee reliable data delivery before deadlines as long as the incoming traffic rates are within the derived maximum network capacity region. This feature not only can lead to high network throughput for the IoNT, but also guarantees that the memory of each device is empty before the next packet arrives, thus addressing the fundamental challenge imposed by the extremely limited memory of nano-devices. In addition, the optimal deadline is derived, which guarantees that all the nano-devices can achieve perpetual communications by jointly considering the energy consumption of communications over the terahertz channel and energy harvesting based on piezoelectric nano-generators.

Wireless underground sensor networks (WUSNs) present a variety of new research challenges. Magnetic induction (MI)-based transmission has been proposed to overcome the very harsh propagation conditions in underground communications in recent years. In this approach, induction coils are utilized as antennas in the sensor nodes. This solution achieves larger transmission ranges compared with the traditional electromagnetic wave-based approach. In the past, some efforts have been made to characterize the signal transmission in MI-WUSNs. Those investigations, however, mostly refer to the information transmission. One of the open issues that may constrain the system design in some of the applications is the powering of the individual sensor nodes. Due to the low accessibility of the nodes, a new method of wireless power transfer for MI-WUSNs is proposed in this paper. This method is mainly based on simultaneous signal transmissions from multiple sensor nodes with optimized signal constellations. Furthermore, the optimal scheduling for power transmission and reception is provided, which maximizes the energy efficiency of the network charging procedure. The proposed method is compared with the naive approaches and shows a significant improvement of the system performance in terms of energy efficiency.

Cellular systems are rapidly evolving from a homogeneous macrocell deployment to a heterogeneous deployment of macrocells overlaid with many small cells. The striking features of small cells include small coverage area, ad-hoc deployment, and flexible backhaul connectivity. These features call for a profound rethinking of traditional cellular concepts including mobility management and interference management among others. Owing to the unique features, coordinated small cells or commonly referred to as network of small cells promises several benefits including efficient mobility management in a rapid and scalable fashion. The problem of handover in a high-density small cell deployment is studied in this work. A novel local anchor-based architecture for a static cluster of small cells is proposed using which new handover schemes are presented. Such clusters are prevalent in the evolving cellular systems involving high-density small cell deployments in urban, residential, and enterprise environments. A mathematical framework is developed using discrete-time-Markov-models to evaluate the proposed schemes. Using this, closed-form expressions for key handover metrics including handover cost and interruption time are derived. Extensive numerical and simulation studies indicate significant savings of over 50 percent in the handover costs and, more importantly, up to 80 percent in the handover interruption time compared to the existing 3GPP scheme for coordinated small cells.

Existing location management (LM) methods for macrocells in LTE-Advanced have tracking area list (TAL) granularity. Therefore, a user equipment (UE) triggers a location update (LU) whenever it leaves its current TAL, and it is searched through paging (PG) with TAL accuracy. However, these procedures are not well-suited for small cells (SCs). The reasons are twofold. First, dense deployments of SCs imply that paging has a low probability to be successful in the first attempt, increasing the signaling overhead in the core network (CN). Second, smaller coverage areas lead to a higher mobility among cells, increasing the signaling overhead in the CN due to LUs. In this work, two LM schemes with fine granularity are proposed. These schemes update UE's location to a local anchor (LA) in a SC or tracking area (TA) basis, respectively. By increasing the accuracy of UE's location, a significant reduction of signaling overhead in the CN due to PG is achieved. Moreover, LUs to the LA are performed through direct X2-interface links to avoid signaling overhead in the CN. A versatile mobility model is developed and closed-form expressions for UEs' mobility metrics are found to validate the proposed schemes through variations of critical parameters such as TA/TAL configuration, UE's mobility patterns and cell residence times.

Multi-stream carrier aggregation (MSCA) has been recently proposed as a mechanism to increase the amount of bandwidth available to users for heterogeneous networks (HetNets) in 5G wireless systems. Previous studies have focused only on maximizing the network capacity and fairness, without considering the energy efficiency of the MSCA. In this paper, the use of MSCA to minimize the energy consumption in a multi-layer HetNet is studied. The convexity of the energy minimization problem is examined, leading to the need of a quasi-convex relaxation. With this approximation, an algorithm bisection method for energy minimization is designed to solve the energy minimization problem and obtains an optimum cell-association policy. Since the operators are generally interested in a balance between the energy minimization and capacity maximization, such multi-objective optimization is needed, and we studied it in this paper. The two aforementioned conflicting objectives can be jointly analyzed and solved through scalarization, even though the energy minimization has a quasi-convex objective function, and not a convex one. Performance evaluation is provided to identify the achievable energy savings of our proposed algorithm and to characterize the tradeoffs between the energy minimization and capacity maximization in a multi-layer HetNet in 5G systems that support MSCA.

Magnetic induction (MI) based communication and power transfer systems have gained an increased attention in the recent years. Typical applications for these systems lie in the area of wireless charging, near-field communication, and wireless sensor networks. For an optimal system performance, the power efficiency needs to be maximized. Typically, this optimization refers to the impedance matching and tracking of the split-frequencies. However, an important role of magnitude and phase of the input signal has been mostly overlooked. Especially for the wireless power transfer systems with multiple transmitter coils, the optimization of the transmit signals can dramatically improve the power efficiency. In this work, we propose an iterative algorithm for the optimization of the transmit signals for a transmitter with three orthogonal coils and multiple single coil receivers. The proposed scheme significantly outperforms the traditional baseline algorithms in terms of power efficiency.

Terahertz (0.1-10 THz) band communication is envisioned as a key technology to satisfy the increasing demand for ultra-high-speed wireless links. In this paper, a three dimensional (3D) end-to-end model is developed, which includes the graphene-based antenna response and the channel model in the THz band. The developed theoretical model is validated with COMSOL simulations. By using the developed 3D end-to-end model, an in-depth analysis on the 3D channel characteristics is carried out. In particular, the use of a 13-dB-gain antenna leads to the decrease of the delay spread from 0.2 ns to 3.2 ps, and the decrease of the angular spread by a factor of 20. The resulting coherence bandwidth reaches 63 GHz. A target capacity of 100 Gbps can be achieved with the directional antenna for the distance of 0.4m over 0.8-0.9 THz, which is unreachable with the isotropic antenna. However, the directivity is at the cost of the strict antenna alignment, and the deviation needs to be smaller than 12.4o. The provided analysis lays out the foundation for reliable and efficient ultra-high-speed wireless communications in the THz band.

Wireless underground sensor networks (WUSNs) present a variety of new research challenges. Magnetic induction (MI) based transmission has been proposed to overcome the very harsh propagation conditions in underground communications in recent years. In this approach, induction coils are utilized as antennas in the sensor nodes. This solution achieves longer transmission ranges compared to the traditional electromagnetic (EM) waves based approach. Furthermore, a passive relaying technique has been proposed in the literature where additional resonant circuits are deployed between the nodes. However, this solution is shown to provide only a limited performance improvement under practical system design contraints. In this work, the potential of an active relay device is investigated which may improve the performance of the system by combining the benefits of the traditional wireless relaying and the MI based signal transmission.

The objective of Wireless Underground Sensor Networks (WUSNs) is to establish an efficient wireless communication in the underground medium. A magnetic induction (MI)-based signal transmission scheme has been proposed to overcome the very harsh propagation conditions in WUSNs. Due to a much lower vulnerability to the environmental changes, the MI technique has been shown to improve the system performance in terms of achievable data rates and coverage compared to the traditional EM wave based transmission. Two different approaches are known from the literature: direct MI transmission and MI waveguides, where many resonant relay circuits are deployed in the latter between the two nodes to be connected. In this work, digital transmission schemes are investigated for MI-WUSNs employing these two approaches. The influence of transmission parameters like symbol duration and modulation scheme are studied and new methods for their optimization are proposed. In this context, significant gains can be achieved compared to the naive straightforward approaches.

Electromagnetic communication at the nanoscale has, to date, been studied in either the very high frequency (VHF) (30–300 MHz) or in the TeraHertz band (0.1–10 THz). The main focus of this paper is on electromagnetic communication in the VHF band and determining the bit error rate (BER) performance of nanoscale receivers utilizing a carbon nanotube (CNT). To determine BER performance, statistical characterization of an average-level detector output is obtained for two different receiver configurations: nanotube receiver, and tunneling nanotube receiver. For the nanotube receiver, the linear component not considered in the previous studies is included and shown to significantly affect the variance of the detector output and, also, exact analysis is performed with some significant differences to previous approximations. The tunneling nanotube receiver, for which no statistical characterization has been done to date, is analyzed. Extensive simulation studies are presented to confirm the accuracy of the theoretical results provided for the distribution of the average-level detector output. The feasible communication distances are investigated based on the BER performance by using realistic system parameters. The results reveal the potential usage of the VHF band in nanonetworks and highlight the importance of maximizing the charge at the CNT tip.

Molecular Communication (MC) is a nano-scale communication paradigm where the information is carried by molecular signals. To establish information transmission using molecules, biological nanomachines can be utilized as transmitters and receivers. A bacteria can be programmed as a biotransceiver by modifying their genetic code to implement biological circuits. In this paper, genetically engineered bacteria-based biotransceivers are investigated for MC, where bacteria can generate and respond to the molecular signals. A biochemical model of biological circuits is presented, and both analog and digital signaling are studied. The challenges in connecting basic biological circuits to build these blocks are revealed. A biotransceiver architecture is introduced that combines sensing, transmitting, receiving and processing blocks. Furthermore, biological circuit design framework is proposed for transmission of signals with M-ary pulse amplitude modulation. The biological circuits designed for biotransceiver are elaborated via numerical results based on biochemical parameters of the genetically engineered bacteria. The provided results show that using biological circuits, bacteria can function as a transmitter and receiver node for MC. Our work stands as a basis for future biotransceiver design for MC.

Cellular network technologies have traditionally evolved to meet the ever-increasing need for capacity and coverage. Particularly, there has been a significant focus on exploiting the use of small cells and heterogeneous networks (HetNets). In the latter, the economic and environmental impact of the energy consumption is a key concern. Although much research has been done to address the energy consumption in HetNets, existing approaches have failed to capture the key factors affecting it. In this paper, the energy consumption in HetNets is analyzed with a focus on their multi-layer nature and the dependence of the energy consumption on the spatio-temporal traffic demands and the internal base station hardware components. The problem of minimizing the energy consumption is then studied and characterized in terms of a 0-1 Knapsack-like problem. Due to the differences with the classical 0-1 Knapsack problem, an efficient algorithm is introduced to minimize the energy consumption by adjusting the cell-association and the base stations on-off policies. Such algorithm is shown to be applicable to the twoand m-layer HetNet cases. Performance evaluation is provided to identify the achievable energy savings of our algorithm and its effect on the energy consumption, activity, and load across multiple layers.

In the last several years, many algorithms trying to mimic biological processes have been proposed to enhance the performance of communication networks. However, the bio-inspired algorithms represent only the very first step toward the design of a smart adaptive communication network since: 1) they model only a limited set of the rules underlying the biological processes, thus, omitting fundamental functionalities; 2) they are executed on traditional computer architectures, thus, failing to achieve the intrinsic parallelism exhibited by biological processes. To overcome these issues, in this paper, the BioNetwork paradigm is proposed, a novel communication network paradigm in which the traditional network nodes are replaced by living organisms. The BioNetwork paradigm provides very attractive features over traditional network paradigms, such as efficiency, adaptivity, reliability, self-organization, and scalability. Moreover, it has a huge potential since it can be adopted in many different applications, such as health and military ones. In the paper, this potential is shown by proving that a BioNetwork can solve one of the most fundamental NP-hard problems in networks, i.e., the Steiner tree problem. To this aim, a BioNetwork constituted by a unicellular organism, the Physarum polycephalum slime mold, is designed. Throughout the paper, it is proven that a Physarum BioNetwork can solve the Steiner tree problem with an exponential convergence rate toward the optimal solution. The theoretical solutions are validated through a case study.

Terahertz (0.06-10 THz) Band communication is envisioned as a key technology for satisfying the increasing demand for ultra-high-speed wireless links. In this paper, first, a unified multi-ray channel model in the THz Band is developed based on ray tracing techniques, which incorporates the propagation models for the line-of-sight, reflected, scattered, and diffracted paths. The developed theoretical model is validated with the experimental measurements (0.06-1 THz) from the literature. Then, using the developed propagation models, an in-depth analysis on the THz channel characteristics is carried out. In particular, the distance-varying and frequency-selective nature of the Terahertz channel is analyzed. Moreover, the coherence bandwidth and the significance of the delay spread are studied. Furthermore, the wideband channel capacity using flat and water-filling power allocation strategies is characterized. Additionally, the temporal broadening effects of the Terahertz channel are studied. Finally, distance-adaptive and multi-carrier transmissions are suggested to best benefit from the unique relationship between distance and bandwidth. The provided analysis lays out the foundation for reliable and efficient ultra-high-speed wireless communications in the (0.06-10) THz Band.

Wireless underground sensor networks (WUSNs) enable many applications such as underground pipeline monitoring, power grid maintenance, mine disaster prevention, and oil upstream monitoring among many others. While the classical electromagnetic waves do not work well in WUSNs, the magnetic induction (MI) propagation technique provides constant channel conditions via small size of antenna coils in the underground environments. In this paper, instead of adopting currently layered protocols approach, a distributed cross-layer protocol design is proposed for MI-based WUSNs. First, a detailed overview is given for different communication functionalities from physical to network layers as well as the QoS requirements of applications. Utilizing the interactions of different layer functionalities, a distributed environment-aware protocol, called DEAP, is then developed to satisfy statistical QoS guarantees and achieve both optimal energy savings and throughput gain concurrently. Simulations confirm that the proposed cross-layer protocol achieves significant energy savings, high throughput efficiency and dependable MI communication for WUSNs.

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Terahertz Band (0.1-10 THz) communication is envisioned as a key technology to satisfy the increasing demand for ultra-broadband wireless communication. THz Band communication will alleviate the spectrum scarcity and capacity limitations of current wireless systems, and enable new applications both in classical networks and novel nanoscale networks. In this paper, a novel distance-aware multi-carrier (DAMC) modulation scheme is developed for both single-transmitter single-receiver and single-transmitter multiple-receiver cases in THz Band communication. The developed DAMC modulation scheme takes advantage of the distance- and frequency-dependent channel peculiarities, and provides adaptive utilization of the ultra-broad bandwidth in the THz Band. Furthermore, the data rates of the DAMC scheme are analytically investigated, numerically evaluated, and compared with existing single-band pulse-based modulation and fixed-bandwidth adaptive modulation. The results show that data rates can be improved by one order of magnitude by using the DAMC scheme, at the costs of design complexity for the control unit, multi-carrier modulator and channel feedback path.

Wireless underground sensor networks (WUSNs) are an emerging and promising research area. The aim of WUSNs is to establish an efficient wireless communication in the underground medium. A magnetic induction (MI)-based waveguide technique has been proposed to overcome the very harsh propagation conditions in WUSNs. In this approach, several resonant relay circuits are deployed between the two nodes to be connected. This technique allows for an extension of the transmission range. In this work, we investigate digital transmission schemes for MI-WUSNs. We analyze the influence of transmission parameters like symbol duration and modulation scheme and propose methods for their optimization.

Oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance are typical applications for wireless underwater sensor networks. In this talk wireless underwater acoustic communication channel is explored, novel medium access control and routing protocols will be presented. On the other hand, sensor applications in soil media and tunnels have unique communication problems. In particular, the wireless channel pecularities in the underground make communication problems interesting which will be discussed in this talk. Electromagnetic and Magnetic Induction communication paradigms are explored. Future research challenges will be highlighted in both areas.

Molecular communication (MC) between a transmitter and a receiver placed in the chambers attached to a microfluidic channel is investigated. A linear end-to-end channel model is developed capturing the effects of the diffusion and the junction transition at the chambers, as well as the microfluidic channel shapes and the fluid flow. The spectral density of the propagation noise is studied, and the flat frequency bands are identified for the chambers and the microfluidic channel. This suggests that in certain microfluidic design choices, the spectral density of noise may end up naturally being flat. Motivated by this result, the additive white Gaussian noise (AWGN) model is developed based on the chamber, the microfluidic channel, and the fluid flow parameters for the end-to-end propagation noise. Furthermore, the molecular memory is modeled due to inter-diffusion among transmitted molecular signals. The effect of the molecular memory on the end-to-end propagation noise is also analyzed. To substantiate our analytical results, the ranges of physical parameters that yield a linear end-to-end MC channel are investigated. These results show the validity of the AWGN model for MC over microfluidic channels and characterize the impact of the microfluidic channel and chamber geometry on the propagation noise and memory.

Particulate Drug Delivery Systems (PDDS) are therapeutic methods that use nanoparticles to achieve their healing effects at the exact time, concentration level of drug nanoparticles, and location in the body, while minimizing the effects on other healthy locations. The Molecular Communication (MC) paradigm, where the transmitted message is the drug injection process, the channel is the cardiovascular system, and the received message is the drug reception process, has been investigated as a tool to study nanoscale biological and medical systems in recent years. In this paper, the various noise effects that cause uncertainty in the cardiovascular system are analyzed, modeled, and evaluated from the information theory perspective. Analytical MC noises are presented to include all end-to-end noise effects, from the drug injection, to the absorption of drug nanoparticles by the diseased cells, in the presence of a time-varying and turbulent blood flow. The PDDS capacity is derived analytically including all these noise effects and the constraints on the drug injection. The proposed MC noise is validated by using the kinetic Monte-Carlo simulation technique. Analytical expressions of the noise and the capacity are derived, and MC is presented as a framework for the optimization of particulate drug delivery systems (PDDS).

Nanonetworks consist of nano-sized communicating devices which are able to perform simple tasks at the nanoscale. Nanonetworks are the enabling technology of long-awaited applications such as advanced health monitoring systems or high-performance distributed nano-computing architectures. The peculiarities of novel plasmonic nano-transceivers and nano-antennas, which operate in the Terahertz Band (0.1-10 THz), require the development of tailored communication schemes for nanonetworks. In this paper, a modulation and channel access scheme for nanonetworks in the Terahertz Band is developed. The proposed technique is based on the transmission of one-hundred-femtosecond-long pulses by following an asymmetric On-Off Keying modulation Spread in Time (TS-OOK). The performance of TS-OOK is evaluated in terms of the achievable information rate in the single-user and the multi-user cases. An accurate Terahertz Band channel model, validated by COMSOL simulation, is used, and novel stochastic models for the molecular absorption noise in the Terahertz Band and for the multi-user interference in TS-OOK are developed. The results show that the proposed modulation can support a very large number of nano-devices simultaneously transmitting at multiple Gigabits-per-second and up to Terabits-per-second, depending on the modulation parameters and the network conditions.

Wireless underground sensor networks (WUSNs) present a variety of new research challenges. Recently, a magnetoinductive (MI) waveguide technique has been proposed to cope with the very harsh propagation conditions in WUSNs. This relay-based approach allows for an extension of the transmission range, which can be quite limited if relays are not deployed. In this paper, tree-based WUSNs are considered. The objective of our work is to determine the optimal system parameters, topology, and deployment strategy in order to avoid bottlenecks in the system and achieve optimal network throughput. We compare two different deployment schemes: MI waveguides and direct MI transmission (no relays deployed) based connections between sensors. The two schemes are different in nature and propagation characteristics. Therefore, different optimization techniques are utilized. The optimal set of system parameters is chosen to maximize the channel capacity of the worst link and therefore optimize the available data rate. The bottleneck throughput of the direct MI transmission based network can be then compared with the respective results of the MI waveguides based network. In several cases, we observe a better performance of the direct MI transmission based networks.

Molecular nanonetworks stand at the intersection of nanotechnology, biotechnology, and network engineering. The research on molecular nanonetworks proposes the interconnection of nanomachines through molecule exchange. Amongst different solutions for the transport of molecules between nanomachines, the most general is based on free diffusion. The objective of this paper is to provide a statistical-physical modeling of the interference when multiple transmitting nanomachines emit molecules simultaneously. This modeling stems from the same assumptions used in interference study for radio communications, namely, a spatial Poisson distribution of transmitters having independent and identically distributed emissions, while the specific molecule emissions model is in agreement with a chemical description of the transmitters. As a result of the property of the received molecular signal of being a stationary Gaussian Process (GP), the statistical-physical modeling is operated on its Power Spectral Density (PSD), for which it is possible to obtain an analytical expression of the log-characteristic function. This expression leads to the estimation of the received PSD probability distribution, which provides a complete model of the interference in diffusion-based molecular nanonetworks. Numerical results in terms of received PSD probability distribution and probability of interference are presented to compare the proposed statistical-physical model with the outcomes of simulations.

The heavy tailed (HT) traffic from wireless users, caused by the emerging Internet and multimedia applications, introduces a HT interference region within which network users will experience unbounded delay with infinite mean and/or variance. Specifically, it is proven that, if the network traffic of primary networks (e.g., cellular and Wi-Fi networks) is heavy tail distributed, there always exists a critical density λpsuch that, if the density of primary users is larger than λp, the secondary network users (e.g., sensor devices and cognitive radio users) can experience unbounded end-to-end delay with infinite variance even though there exists feasible routing paths along the network users. To counter this problem, the mobility of network users is utilized to achieve delay-bounded connectivity, which simultaneously ensures the existence of routing paths and the finiteness of the delay variance along these paths. In particular, it is shown that there exists a critical threshold on the maximum radius that the secondary user can reach, above which delay-bounded connectivity is achievable in the secondary networks. In this case, the end-to-end latency of secondary users is shown to be asymptotically linear in the Euclidean distance between the transmitter and receiver.

Wireless Underground Sensor Networks (WUSNs) present a variety of new research challenges. Recently, a magneto-inductive (MI) waveguide technique has been proposed to cope with the very harsh propagation conditions in WUSNs. This approach allows for an extension of the transmission range, which can be quite limited if relays are not deployed. In this paper, tree-based WUSNs are considered with sensors connected via MI-waveguides. The objective of our work is to determine the optimal system parameters and topology in order to avoid bottlenecks in the system and achieve optimal network throughput.

Smallcell technology is gaining significance as part of the next-generation cellular systems due to their performance benefits in terms of increased network capacity and improved indoor and local coverage. Hybrid access smallcells, which provide service to both indoor as well as neighboring users, adopt adhoc policies to guarantee performance benefits to indoor home users in the presence of external neighboring users. Such policies must be able to stabilize user queues as well as to provision performance benefits in terms of delay and throughput, especially for the indoor users. As a result, classification of user data in terms of traffic type and user type is required to effectively achieve the differentiated QoS performance. In this paper, a traffic-aware utility function is proposed, which takes into account for the user's priority index and traffic characteristics to efficiently provide differentiated QoS benefits to users served under an OFDMA hybrid smallcell. The problem of the traffic-aware utility based scheduling under power constraints is posed as an optimization objective and an optimal algorithm for the scheduling problem is presented. The results show that the proposed scheme achieves QoS performance benefits in terms of throughput and delay.

Recent interest in same-frequency/same-time full-duplex radio frequency communication has led to the study of self-interference cancellation methods for a co-located transmitter and receiver pair. So far, important practical aspects of self-interference cancellation have not been considered, such as receiver amplifier saturation and dynamic range, which extend the minimum distance between transmit and receive antennas without sufficient interference isolation. Further, current solutions lack significant self-interference attenuation for wideband signals. In this paper, a method for canceling a passband self-interference signal using adaptive filtering in the digital domain is presented. Based on acoustic active noise cancellation foundations, a cancellation signal is created that destructively combines with the undesired self-interference signal in the passband, taking into account differences in the complex passband nature of RF signals versus the baseband nature of acoustic signals. The efficacy of this interference cancellation scheme is compared to other self-interference cancellation architectures in the literature including digital as well as other active passband approaches. It is shown that for high-power wideband transmission signals, this adaptive active analog cancellation method effectively reduces the self-interference signal while satisfying practical constraints set by transceiver hardware. It is also shown that this approach decreases the minimum distance between the transmit and receive antennas or allows higher transmission power, thereby extending the range of a full-duplex device.

The energy consumption reduction in cellular systems is important from both economic and environmental perspectives. Nearly 80% of the energy in cellular systems is consumed by the Radio Access Network (RAN). In recent years, much research has been done to reduce the energy consumption in the RAN. However, existing models fail to capture the spatiotemporal variability of traffic demands, bit rate and power requirements, as well as the peculiarities in the energy consumption from different hardware components in a base station (BS). In this paper, a new RAN energy consumption model for multi-layer infrastructure-based heterogeneous wireless systems (IbHWS) is proposed. It captures all the aforementioned factors and accurately addresses the characteristics of IbHWS, where cellular systems are a particular case. A low-complexity algorithm is proposed to minimize the RAN's energy consumption, and to satisfy all traffic demands in space and time. Based on extensive simulation results across a wide range of scenarios, the energy savings from this algorithm were on average 26%.

Wireless Underground Sensor Networks (WUSNs) present a variety of new research challenges. Recently a magneto-inductive (MI) waveguide technique has been proposed to overcome the very harsh propagation conditions in WUSNs. In this approach, several resonant relay circuits are deployed between the two nodes to be connected. This technique allows for an extension of the transmission range, which can be quite limited, if relays are not deployed. In this paper, channel and noise models for MI-WUSNs using MI-waveguides are developed. Results of a numerical evaluation of the channel capacity under practical constraints are provided and the influence of the system parameters on the performance is discussed.

A key issue of the spectrum sensing functionality in Cognitive Radio (CR) networks is the ability of tuning the sensing time parameters, i.e., the sensing time and the transmission time, according to the Primary User (PU) network dynamics. In fact, these parameters influence both the spectrum sensing efficiency and the PU interference avoidance. This issue becomes even more challenging in presence of PU mobility. In this paper, an optimal spectrum sensing design for mobile PU scenarios is proposed with the aim to achieve the following important features: i) to determine the optimal mobility-aware transmission time, i.e., the transmission time value that jointly maximizes the spectrum sensing efficiency and satisfies the PU interference constraint; ii) to determine the optimal mobility-aware sensing time threshold, i.e., the maximum sensing time value assuring efficient spectrum sensing. First, closed-form expressions of both the optimal transmission time and the optimal sensing time threshold are analytically derived for a general PU mobility model. Then, the derived expressions are specialized for two widely adopted mobility models, i.e., the Random Walk mobility Model with reflection and the Random Way-Point mobility Model. Practical rules for the sensing parameter tuning are provided with reference to the considered mobility models. The analytical results are finally validated through simulations.

Nanonetworks, i.e., networks of nano-sized devices, are the enabling technology of long-awaited applications in the biological, industrial and military fields. For the time being, the size and power constraints of nano-devices limit the applicability of classical wireless communication in nanonetworks. Alternatively, nanomaterials can be used to enable electromagnetic (EM) communication among nano-devices. In this paper, a novel graphene-based nano-antenna, which exploits the behavior of Surface Plasmon Polariton (SPP) waves in semi-finite size Graphene Nanoribbons (GNRs), is proposed, modeled and analyzed. First, the conductivity of GNRs is analytically and numerically studied by starting from the Kubo formalism to capture the impact of the electron lateral confinement in GNRs. Second, the propagation of SPP waves in GNRs is analytically and numerically investigated, and the SPP wave vector and propagation length are computed. Finally, the nano-antenna is modeled as a resonant plasmonic cavity, and its frequency response is determined. The results show that, by exploiting the high mode compression factor of SPP waves in GNRs, graphene-based plasmonic nano-antennas are able to operate at much lower frequencies than their metallic counterparts, e.g., the Terahertz Band for a one-micrometer-long ten-nanometers-wide antenna. This result has the potential to enable EM communication in nanonetworks.

In this paper, the problem of resource allocation optimization is studied for a single-cell multiuser cognitive radio network in the presence of primary user networks. The spectral access of the cognitive radio network is based on Orthogonal Frequency Division Multiple Access (OFDMA). A joint bandwidth and power allocation is performed so that users' rate requirements are satisfied, and the integrity of primary user communication is preserved. In this work, two unique challenges are addressed. The first is the incorporation of primary user activity in the design of resource allocation technique, and the second is the limited hardware capabilities of cognitive terminals compared to those available at the cognitive base station. To address these problems, a novel resource allocation framework is proposed based on the bandwidth-power product minimization, which is an effective metric in evaluating the spectral resource consumption in a cognitive radio environment. The framework takes into consideration the challenges aforementioned. The results show significant enhancement in spectral efficiency by using our framework compared to classical power adaptive optimization using iterative waterfilling scheme.

The heavy tailed nature exhibited in both primary and secondary users' traffic fundamentally challenges the performance limit of dynamic spectrum access (DSA) networks under the conventional light tailed assumptions. This paper provides an asymptotic analysis of the steady-state queue length distribution of secondary users (SUs) under the heavy tailed network environment. Specifically, two network scenarios are investigated. In the first scenario where each SU has its exclusive access to a primary user (PU) channel, it is shown that the heavy tailed nature of either the PU traffic or the SU traffic can make SUs experience heavy tailed queue length with unbounded moments. In the second scenario where multiple SUs share a single PU channel, the queuing performance under throughput optimal scheduling policies is studied. It is proven that if the PU traffic has a heavier tail than any SU traffic, the queue length of each SU is at least one order heavier than the PU traffic under any scheduling policy. Otherwise, if the traffic from at least one of the SUs has a heavier tail than the PU traffic, it is proven that the celebrated throughput-optimal maximum weight scheduling leads to the worst possible asymptotic queuing performance for SUs by letting each SU queue have the heaviest possible tail. On the contrary, it is shown that there always exists a feasible set of β parameters such that the maximum weight-β scheduling yields the best asymptotic performance for the SU queues by letting each queue have the lightest possible tail.

Magnetic Induction (MI) techniques enable efficient wireless communications in dense media with high material absorptions, such as underground soil medium and oil reservoirs. A wide range of novel and important applications in such RF-challenged environments can be realized based on the MI communication mechanism. Despite the potential advantages, the major bottleneck of the MI communication is the limited channel capacity due to the low MI bandwidth. In this paper, the Spread Resonance (RS) strategy is developed for the MI communication in RF-challenged environments which greatly increases the MI channel capacity. Specifically, instead of using the same resonant frequency for all the MI coils, the spread resonance strategy allocates different resonant frequencies for different MI relay and transceiver coils. An optimization solution for the resonant frequency allocation is formulated to maximize the MI channel capacity which captures multiple unique MI effects, including the parasitic capacitor in each MI coil, the Eddy currents in various transmission media with limited conductivities, and the random direction of each coil. Numerical evaluations are provided to validate the significant channel capacity improvements by the proposed SR strategy for MI communication systems.

Molecular Communication (MC) is a communication paradigm based on the exchange of molecules. The implicit biocompatibility and nanoscale feasibility of MC make it a promising communication technology for nanonetworks. This paper provides a closed-form expression for the information capacity of an MC system based on the free diffusion of molecules, which is of primary importance to understand the performance of the MC paradigm. Unlike previous contributions, the provided capacity expression is independent from any coding scheme and takes into account the two main effects of the diffusion channel: the memory and the molecular noise. For this, the diffusion is decomposed into two processes, namely, the Fick's diffusion and the particle location displacement, which are analyzed as a cascade of two separate systems. The Fick's diffusion captures solely the channel memory, while the particle location displacement isolates the molecular noise. The MC capacity expression is obtained by combining the two systems as function of the diffusion coefficient, the temperature, the transmitter-receiver distance, the bandwidth of the transmitted signal, and the average transmitted power. Numerical results show that a few kilobits per second can be reached within a distance range of tenth of micrometer and for an average transmitted power around 1 pW.

Cognitive Radio (CR) networks allow users to opportunistically transmit in the licensed spectrum bands, as long as the performance of the Primary Users (PUs) of the band is not degraded. Consequently, variation in spectrum availability with time and periodic spectrum sensing undertaken by the CR users have a pronounced effect on the higher layer protocol performance, such as at the transport layer. This paper investigates the limitations of classical TCP newReno in a CR ad hoc network environment, and proposes TCP CRAHN, a window-based TCP-friendly protocol. Our approach incorporates spectrum awareness by a combination of explicit feedback from the intermediate nodes and the destination. This is achieved by adapting the classical TCP rate control algorithm running at the source to closely interact with the physical layer channel information, the link layer functions of spectrum sensing and buffer management, and a predictive mobility framework that is developed at the network layer. An analysis of the expected throughput in TCP CRAHN is provided, and simulation results reveal significant improvements by using our approach. To the best of our knowledge, our approach takes the first steps toward the design of a transport layer for CR ad hoc networks.

In wireless multimedia sensor networks (WMSNs), visual correlation exists among multiple nearby cameras, thus leading to considerable redundancy in the collected images. This paper proposes a differential coding-based scheduling framework for efficiently gathering visually correlated images. This framework consists of two components including MinMax Degree Hub Location (MDHL) and Maximum Lifetime Scheduling (MLS). The MDHL problem aims to find the optimal locations for the multimedia processing hubs, which operate on different channels for concurrently collecting images from adjacent cameras, such that the number of channels required for frequency reuse is minimized. After associating camera sensors with proper hubs, the MLS problem targets at designing a schedule for the cameras such that the network lifetime of the cameras is maximized by letting highly correlated cameras perform differential coding on the fly. It is proven in this paper that the MDHL problem is NP-complete, and the MLS problem is NP-hard. Consequently, approximation algorithms are proposed to provide bounded performance. Since the designed algorithms only take the camera settings as inputs, they are independent of specific multimedia applications. Experiments and simulations show that the proposed differential coding-based scheduling can effectively enhance the network throughput and the energy efficiency of camera sensors.

New propagation techniques using magnetic induction (MI) waveguide solves the problems of traditional techniques in many challenged environments, such as underground, mines/tunnels, and oil reservoirs. However, deploying MI waveguides to connect the wireless nodes in such networks is challenging due to the high deployment cost, the complex shape of the communication range of the MI waveguides, and the significant impacts of the node failure and relay coil displacement. To date, the deployment problems in the MI-based networks have not been addressed. In this paper, the optimal MI waveguide deployment strategies are investigated in both one and two dimensional MI-based networks where the nodes are distributed either randomly or according to a regular lattice. Validated by both theoretical deduction and simulations, the proposed deployment strategies can construct a reliable MI-based network that is robust to node failure and relay coil displacement with minimum cost.

Future enhanced oil recovery technology requires wireless sensor networks to effectively operate in underground oil reservoirs. In this case, the millimeter scale sensor nodes with the antennas at the same scale have to be deployed in the confined underground oil reservoir fractures. This necessitates the sensor nodes to be operating in the THz frequency range. In this paper, the propagation based on electromagnetic (EM) waves in the Terahertz band (0.1-120.0 THz) through a crude oil/water mixture and soil medium is analyzed in order to explore its applicability in underground oil reservoir assessments. The developed model evaluates the total path loss and the absorption loss that an EM wave experiences when propagating through the crude oil/water mixture and soil medium. Our results show that sensors can communicate successfully for distances up to 1 centimeter and we have determined the existence of two transmission bands, in which the path loss is below 100 dB. Among those, the frequency window, which provides best performance, determined as 70 to 85 THz. Different path and absorption loss schemes considered, which suggests that the 70 to 85 THz band is suitable for sensor communications in a medium of crude oil/water mixture and soil.

In Cognitive Radio (CR) Networks, the licensed but vacant spectrum bands are shared by the unlicensed users (CR users) in an opportunistic manner. The CR users should operate and cohabit in the licensed bands without causing any interference to the Primary Users (PUs). This CR user cohabitation which is managed by a spectrum coordinator, enables several design challenges. Therefore, A User Cohabitation Coordinator, UCC, should be designed considering the heterogeneous Quality of Service (QoS) requirements for the CR users and the short-term fluctuations in the available licensed spectrum bands. Moreover, the spectrum coordination among the CR network operators for CR users should also be considered by the UCC for an effective and fair spectrum sharing. Considering these challenges, the main contribution of this paper is to design a QoS-based spectrum coordinator for CR user cohabitation in order to achieve high throughput and fairness. The proposed UCC uses the first-difference filter clustering and correlation based PU modeling to integrate the fluctuations of the PU activities into the spectrum sharing. The UCC characterizes the QoS requirements of CR users by adopting queuing theoretic models. The proposed scheme enables the cohabitation of the CR operators dynamically. The evaluations demonstrate that the proposed UCC provides high throughput while maintaining the fairness in the CR networks.

Communications based on diffusion refers to the transfer of information using molecules as message carriers whose propagation is governed by the laws of Brownian motion. Molecular communication is considered to be one of the most promising approaches for the end-to-end communication between nanoscale devices. In this paper, both an optimal and a suboptimal receiver detection scheme are proposed for a diffusionbased binary digital communication system in the presence of ISI. The transmission of binary information is accomplished by using On-Off Keying (OOK) with only one molecule. The proposed system can serve as the theoretical basis for end-to-end communication in molecular nanonetworks where molecules of different types are used by different nanoscale devices. The effect of channel memory resulting from the residual molecule diffusion from previous transmissions is treated analytically in the formulation of the detection schemes. Numerical results show that the proposed detection schemes can maximize the mutual information over a practical range of the parameter of signaling interval without a priori information. A channel capacity of 1 bit per channel utilization during a signaling interval can be ultimately achieved by extending the duration of the signaling interval, even with infinite channel memory.

Diffusion-based communication refers to the transfer of information using molecules as message carriers whose propagation is based on the law of molecular diffusion. Path loss can have a major impact on the link quality in molecular communication as the signal strength is shown inversely proportional to the cube of the communication distance. In this paper, various diversity techniques for Multi-Input Multi-Output (MIMO) transmissions based on molecular diffusion are proposed to improve the communication performance in nanonetworks in the presence of Multi-User Interference (MUI). Analogous to radio communication, the concept of diversity and Spatial Multiplexing (SM) can be successfully applied in molecular communication. To the best of our knowledge, our paper is the first which investigates the aspects of MIMO transmissions for molecular communication. Numerical results show that the proposed diversity techniques can successfully lower the error rate. Further performance improvement can be obtained by properly allocating molecules among the transmission nodes if the Channel State Information (CSI) is available at the transmitter end. To optimize the system throughput, a dynamic switching mechanism between the diversity mode and the Spatial Multiplexing (SM) mode can be employed.

Femtocells have emerged as an alternative solution for operators to improve coverage and throughput in indoor environments. However, modeling and development platforms are still needed in order to test implementation-specific characteristics of femtocells, such as interference mitigation techniques and self-organizing algorithms. Using OPNET, a high fidelity simulation environment for wireless networks, a femtocell modeling and development platform is created, closely following the specifications dictated by 3GPP regarding the entities, functionalities, procedures, and message formats for femtocell networks. It is shown how the platform reflects the effect of both interference and backhaul degradation on the overall performance of the network, which represent the key concerns for operators nowadays regarding femtocell deployments.

Graphene-enabled wireless communications set the Terahertz Band as the frequency band of operation of future nanodevices (0.1-10 THz). Amongst others, femtosecond-long pulse-based modulation schemes have been recently proposed to enable the communication among nanodevices. Within this context, a receiver architecture suitable for nanodevices must be ultra compact, must have high sensitivity and must be ultra-low power. Unfortunately, common receiver architectures used in other communication schemes, such as IR-UWB, show a strong compromise between low complexity and performance. In this paper, a novel receiver architecture for pulse-based communication based on a Continuous-time Moving Average (CTMA) symbol detection scheme is presented. This scheme bases its symbol decision on the received signal power maximum peak after the CTMA, which is implemented with a single low-pass filter. Moreover, an analytical model for the symbol detection is provided and it is quantitatively shown that the proposed CTMA scheme outperforms previous symbol detection schemes for pulse-based modulations in terms of Symbol Error Rate (SER). The low complexity and relaxed synchronization needed for this symbol detector makes this structure specially suited for the development of future transceivers for nano-devices.

Control channel jamming is a severe security problem in wireless networks. This results from the fact that the attackers can effectively launch the denial of service attacks by jamming the control channels. Traditional approaches to combating this problem such as channel hopping sequences may not be the secure solution against intelligent attackers because the reliability of control channels in cognitive radio ad hoc networks cannot be guaranteed. In this paper, we introduce a jamming-resilient control channel (JRCC) game to model the interactions among cognitive radio users and the attacker under the impact of primary user activity. We propose the JRCC algorithm that enables user cooperation to facilitate control channel allocations and adapts to primary user activity with variable learning rates using the Win-or-Learn-Fast principle for jamming-resilience in hostile environments. It is shown that the optimal strategies converge to a Nash equilibrium or the expected rewards of the strategies converge to that of a Nash equilibrium. The results also show that the JRCC algorithm effectively combats jamming under the impact of primary user activity and sensing errors. Moreover, the control channel allocation policy can be improved by enhancing transmission and sensing capabilities. The proposed algorithm is scalable and can be applied to multiple users.

Diffusion-based communications refers to the transfer of information using particles as message carriers whose propagation is based on the law of particle diffusion. Though still at an early stage, there have been growing interests and research efforts dedicated to this communication technology. It has been identified that diffusion-based communications is one of the most promising approaches for end-to-end communication between nanoscale devices in the near future. In this paper, the design of a binary digital communication system is proposed based on particle diffusion. Stochastic signaling through On-Off Keying (OOK) for random particle emission and a diffusion channel with memory is considered. The diffusion is considered in the cases of one, two, and three dimensions. The receiver detection problem is formulated by using an information-theoretic approach. The optimal decision threshold for the receiver detection is derived through mutual information maximization for two cases, namely, when the a priori probability of bit transmission is fixed and known to the receiver and when this probability is unknown to the receiver. Numerical results indicate that in the case of diffusion in one or two dimensions, the information of a priori probability plays a key role in optimizing the system performance, while it does not when considering the diffusion in three dimensions.

Molecular Communication (MC) is a bio-inspired paradigm where information is exchanged by the release, the propagation and the reception of molecules. The objective of this paper is to analyze the effects of interference in the most general type of MC system, i.e., the diffusion of molecules in a fluidic medium. The study of the InterSymbol Interference (ISI) and Co-Channel Interference (CCI) is conducted through the analysis of the propagation of signals in a diffusion-based channel. An in-depth analysis of the attenuation and the dispersion of signals due to molecule diffusion allows to derive simple closed-form formulas for both ISI and CCI. In this paper, two different modulation schemes, namely, the baseband modulation and the diffusion wave modulation are considered for the release of molecules in the diffusion-based MC and are compared in terms of interference. It is determined that the diffusion wave modulation scheme shows lower interference values than the baseband modulation scheme. Moreover, it is revealed that the higher is the frequency of the modulating diffusion wave, the lower are the effects of the ISI and the CCI on the communication channel. The obtained analytical results are compared and validated by numerical simulation results.

The magnetic induction (MI)-based wireless underground sensor networks (WUSNs) use the novel MI waveguide technique to establish long range and low cost wireless communications in harsh underground environments, which enable a large variety of novel and important applications. One of the main research challenges is the theoretical study of the channel and network capacities in these networks. Compared to the traditional wireless networks, both the channel and network capacities of MI-based WUSNs have significant different characteristics due to the completely different signal propagation techniques and network geometric structure. Moreover, the usage of multiple resonant MI relay coils in MI-based WUSNs brings more reliability concerns. In this paper, mathematical models are developed to evaluate the channel capacity, network capacity, and the reliability of MI-based WUSNs. Specifically, the closed-form expression for the channel capacity in MI-based WUSNs is first derived to capture the effects of multiple system parameters. Then the network capacity scaling laws of MI-based WUSNs are investigated under different deployment strategies. Finally, the system reliability of MI-based WUSNs in terms of the channel capacity and network capacity is discussed. The results of this paper provide principles and guidelines for the design and deployment of MI-based WUSNs.

Nanotechnology is enabling the development of devices in a scale ranging from one to a few one hundred nanometers. Nanonetworks, i.e., the interconnection of nano-scale devices, are expected to expand the capabilities of single nano-machines by allowing them to cooperate and share information. Traditional communication technologies are not directly suitable for nanonetworks mainly due to the size and power consumption of existing transmitters, receivers and additional processing components. All these define a new communication paradigm that demands novel solutions such as nano-transceivers, channel models for the nano-scale, and protocols and architectures for nanonetworks. In this talk, first the state-of-the-art in nano-machines, including architectural aspects, expected features of future nano-machines, and current developments are presented for a better understanding of the nanonetwork scenarios. Moreover, nanonetworks features and components are explained and compared with traditional communication networks. Novel nano-antennas based on nano-materials as well as the terahertz band are investigated for electromagnetic communication in nanonetworks. Furthermore, molecular communication mechanisms are presented for short-range networking based on ion signaling and molecular motors, for medium-range networking based on flagellated bacteria and nanorods, as well as for long-range networking based on pheromones and capillaries. Finally, open research challenges such as the development of network components, molecular communication theory, and new architectures and protocols, which need to be solved in order to pave the way for the development and deployment of nanonetworks within the next couple of decades are presented.

Two-tier femtocell-based networks have been proposed as an economic solution to improve coverage and capacity in wireless cellular systems. Although widely studied in the literature, interference management in these networks remains as a technical challenge in need of effective solutions. In particular, the interference estimation is a relevant portion of the problem that enables correct operation of interference management schemes relying on this information. In this paper, a novel downlink cross-tier interference estimation approach is proposed based on spatio-temporal correlation techniques. An ordinary Kriging interpolator using Semivariogram Analysis is applied to the interfering signal followed by an autorregressive model. The signal estimation at the interfered users' location is exploited at the radio resource manager of the femtocell or macrocell base station by formulating a resource allocation problem that is solved by means of a heuristic algorithm. A practical procedure implementing this scheme in the network is also proposed. Numerical results show how performance of cross-tier interference management approaches can be optimized by implementing this idea.

The heavy tailed nature in dynamic spectrum networks challenges the applicability of conventional network stability criterions. To encounter this, a new stability criterion, namely moment stability, is introduced, which requires that the queue length of each secondary user has finite moments for every achievable order. Then, the necessary and sufficient conditions for the existence of a resource allocation policy to achieve moment stability are derived. Moreover, the network stability region yielded from these conditions is shown to be directly related to the statistics of secondary user traffics, primary user activities, the number of secondary users contending the spectrum, and the total number of primary user channels available to secondary users. In addition, a throughput-optimal policy, which stabilizes the network for any arrival rates in the stability region, is also introduced. In the end, the impact of the heavy tailed primary user traffic on the network stability is investigated, which shows that the tail heaviness of the primary user traffics determines what types of the network stability are achievable for a dynamic spectrum networks.

This paper develops a solution for the problem of uncorrelated user selection in mobile cognitive radio ad hoc networks, with the objective to increase the performance of cooperative spectrum sensing. For this, a fully distributed user selection algorithm is developed by adaptively selecting uncorrelated cognitive radio users, which is able to account for dynamic changes in the network topology and in the channel conditions. Since the proposed user selection is based on the evaluation of the correlation experienced by the cognitive radio users, it is mandatory to have a parameter able to measure the correlation among them. For this, a spatial correlation coefficient is proposed to express the correlation characteristics of mobile cognitive radio users in different environments. Performance evaluation is conducted through simulations, and the results reveal the benefits of adopting the proposed correlation-aware user selection for cooperative spectrum sensing.

Cognitive radio (CR) networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face several challenges based on the fluctuating nature of the available spectrum, making it more difficult to support seamless communications, especially in CR cellular networks. In this paper, a spectrum-aware mobility management scheme is proposed for CR cellular networks. First, a novel network architecture is introduced to mitigate heterogeneous spectrum availability. Based on this architecture, a unified mobility management framework is developed to support diverse mobility events in CR networks, which consists of spectrum mobility management, user mobility management, and intercell resource allocation. The spectrum mobility management scheme determines a target cell and spectrum band for CR users adaptively dependent on time-varying spectrum opportunities, leading to increase in cell capacity. In the user mobility management scheme, a mobile user selects a proper handoff mechanism so as to minimize a switching latency at the cell boundary by considering spatially heterogeneous spectrum availability. Intercell resource allocation helps to improve the performance of both mobility management schemes by efficiently sharing spectrum resources with multiple cells. Simulation results show that the proposed method can achieve better performance than conventional handoff schemes in terms of both cell capacity as well as mobility support in communications.

This paper provides an asymptotic analysis of the transmission delay experienced by SUs for dynamic spectrum access (DSA) networks. It is shown that DSA induces only light-tailed delay if both the busy time of PU channels and the message size of SUs are light tailed. On the contrary, if either the busy time or the message size is heavy tailed, then the SUs' transmission delay is heavy tailed. For this latter case, it is proven that if one of either the busy time or the message size is light tailed and the other is regularly varying with index \alpha, the transmission delay is regularly varying with the same index. As a consequence, the delay has an infinite mean provided \alpha < 1 and an infinite variance provided \alpha < 2. Furthermore, if both the busy time and the message size are regularly varying with different indices, then the delay tail distribution is as heavy as the one with the smaller index. Moreover, the impact of spectrum mobility and multiradio diversity on the delay performance of SUs is studied. It is shown that both spectrum mobility and multiradio diversity can greatly mitigate the heavy-tailed delay by increasing the orders of its finite moments.

The spatial correlation of visual information retrieved from distributed camera sensors leads to considerable data redundancy in wireless video sensor networks, resulting in significant performance degradation in energy efficiency and quality-of-service (QoS) satisfaction. In this paper, a correlation-aware QoS routing algorithm (CAQR) is proposed to efficiently deliver visual information under QoS constraints by exploiting the correlation of visual information observed by different camera sensors. First, a correlation-aware inter-node differential coding scheme is designed to reduce the amount of traffic in the network. Then, a correlation-aware load balancing scheme is proposed to prevent network congestion by splitting the correlated flows that cannot be reduced to different paths. Finally, the correlation-aware schemes are integrated into an optimization QoS routing framework with an objective to minimize energy consumption subject to delay and reliability constraints. Simulation results demonstrate that the proposed routing algorithm achieves efficient delivery of visual information under QoS constraints in wireless video sensor networks.

Two main issues affect the existing routing metrics for cognitive radio ad hoc networks: i) they are often based on heuristics, and thus they have not been proved to be optimal; ii) they do not account for the route diversity effects, and thus they are not able to measure the actual cost of a route. In this paper, an optimal routing metric for cognitive radio ad hoc networks, referred to as OPERA, is proposed. OPERA is designed to achieve two features: i) Optimality: OPERA is optimal when combined with both Dijkstra and Bellman-Ford based routing protocols; ii) Accuracy: OPERA exploits the route diversity provided by the intermediate nodes to measure the actual end-to-end delay, by taking explicitly into account the unique characteristics of cognitive radio networks. A closed-form expression of the proposed routing metric is analytically derived for both static and mobile networks, and its optimality is proved rigorously. Performance evaluation is conducted through simulations, and the results reveal the benefits of adopting the proposed routing metric for cognitive radio ad hoc networks.

Nanonetworks are networks of devices inherently working and communicating at a scale ranging between one and hundreds of nanometers. The motivation behind these nanonetworks is to enhance the complexity and range of operation of the system, as the nanomachines that will be part of these networks have significant limitations in terms of size and power consumption. Neither classical communication schemes nor protocols used in conventional networks are valid in this new scenario. For instance, synchronization between nodes is a feature commonly required to build a network architecture. In this paper, we propose Quorum Sensing as a valid tool to achieve synchronization in a cluster of nodes of a nanonetwork by means of molecular communication, and in a distributed manner. Quorum Sensing is a mechanism by which bacteria coordinate their behavior, based on the emission and reception of molecules called autoinducers. The authors present the communication aspects of this natural phenomenon, as well as some simulation results that show the performance of Quorum Sensing-enabled entities. As a conclusion, some possible applications are outlined.

This paper investigates the optimal sensor density in Wireless Underground Sensor Networks (WUSNs) to guarantee high monitoring accuracy with minimum deployment cost. In WUSNs, the density of underground sensors is expected to be as low as possible due to the high deployment cost. However, an extremely high density of underground sensors is required to maintain the full connectivity of WUSNs due to the harsh underground channel conditions. This conflict constitutes the greatest challenge to deploy the WUSNs and was not addressed before, to our knowledge. In this paper, a spatio-temporal correlation-based data collection scheme is proposed to release the unfeasible sensor density requirement of the full connectivity in WUSNs. More importantly, an explicit solution for sensor density optimization in WUSNs under the proposed data collection scheme is developed such that the effects of the dynamic underground channel conditions, the spatio- temporal correlations, the network connectivity, and the random or controlled mobility of mobile sinks are captured. The results of this paper provide principles and guidelines for the design and deployment of wireless underground sensor networks.

In this paper, a novel Cognitive Radio Resource Management (RRM) is proposed to improve the spectrum utilization efficiency. In this system, heterogeneous Primary Users (PUs) with multiple features are considered where these PU features are exploited to improve the adaptability in Cognitive Radio (CR) networks and, thus, to design an efficient Cognitive RRM. An optimization framework is developed by considering heterogeneous PUs and variable CR demands while assuring interference protection towards PUs. A suboptimal solution is proposed after showing that an optimal solution is computationally infeasible. Simulation results are conducted in terms of total achieved data rate and satisfaction of CRs requirements.

Nanotechnology is providing the engineering community with a new set of tools to design and manufacture integrated devices just a few hundred nanometers in total size. Communication among these nano-devices will boost the range of applications of nanotechnology in several fields, ranging from biomedical research to military technology or environmental science. Within the different alternatives for communication in the nanoscale, recent developments in nanomaterials point to the Terahertz band (0.1-10 THz) as the frequency range of operation of future electromagnetic nano-transceivers. This frequency band can theoretically support very large bit-rates in the short range, i.e., for distances below one meter. Due to the limited capabilities of individual nano-devices, pulse-based communications have been proposed for electromagnetic nanonetworks in the Terahertz band. However, the expectedly very large number of nano-devices and the unfeasibility to coordinate them, can make interference a major impairment for the system. In this paper, low-weight channel coding is proposed as a novel mechanism to reduce interference in pulse-based nanonetworks. Rather than utilizing channel codes to detect and correct transmission errors, it is shown that by appropriately choosing the weight of a code, interference can be mitigated. The performance of the proposed scheme is analytically and numerically investigated both in terms of overall interference reduction and achievable information rate, by utilizing a new statistical interference model. The results show that this type of network-friendly channel coding schemes can be used to alleviate the interference problem in nanonetworks without compromising the individual user information rate.

Communication via diffusion of molecules is an effective method for transporting information in nanonetworks. In this paper, novel modulation techniques called Concentration Shift Keying (CSK) and Molecule Shift Keying (MSK) are proposed for coding and decoding information of the so-called messenger molecule concentration waves in nanonetworks. The first technique, CSK, modulates the information via the variation in the concentration of the messenger molecules whereas MSK utilizes different types of messenger molecules to represent the information. Using simulation, the performance of these modulation techniques is evaluated in terms of susceptibility to noise and transmission power requirements. The new techniques achieve high channel capacity values, in particular, the MSK technique exhibits more robustness against noise and requires less power.

Sandstorms are serious natural disasters, which are commonly seen in the Middle East, Northern Africa, and Northern China.In these regions, sandstorms have caused massive damages to the natural environment, national economy, and human health. To avoid such damages, it is necessary to effectively monitor the origin and development of sandstorms. To this end, wireless sensor networks (WSNs) can be deployed in the regions where sandstorms generally originate so that sensor nodes can collaboratively perform sandstorm monitoring and rapidly convey the observations to remote administration center. Despite the potential advantages, the deployment of WSNs in the vicinity of sandstorms faces many unique challenges, such as the temporally buried sensors and increased path loss during sandstorms. Consequently, the WSNs may experience frequent disconnections during the sandstorms. This further leads to dynamically changing topology. In this paper, a topology analysis of the WSNs for sandstorm monitoring is performed. Four types of channels a sensor can utilize during sandstorms are analyzed, which include air-to-air channel, air-to-sand channel, sand-to-air channel, and sand-to-sand channel. Based on the channel model solutions, a percolation-based connectivity analysis is performed. It is shown that if the sensors are buried in low depth, allowing sensor to use multiple types of channels improves network connectivity. Accordingly, much smaller sensor density is required compared to the case, where only terrestrial air channels are used. Through this topology analysis a WSN architecture can be deployed for very efficient sandstorm monitoring.

Molecular Communication (MC) is a promising bio-inspired paradigm in which molecules are transmitted, propagated and received between nanoscale machines. One of the main challenges is the theoretical study of the maximum achievable information rate (capacity). The objective of this paper is to provide a mathematical expression for the capacity in MC nanonetworks when the propagation of the information relies on the free diffusion of molecules. Solutions from statistical mechanics and thermodynamics are used to derive a closed-form expression for the capacity as function of physical parameters, such as the size of the system, the temperature and the number of molecules as well as of the bandwidth of the system and the transmitted power. An extremely high order of magnitude of the capacity numerical values demonstrates the enormous potential of the diffusion-based MC systems.

In wireless multimedia sensor networks (WMSNs), visual correlation exist among multiple nearby cameras, thus leading to considerable redundancy in the collected images. This paper addresses the problem of timely and efficiently gathering visually correlated images from camera sensors. Towards this, three fundamental problems are considered, namely, MinMax Degree Hub Location (MDHL), Minimum Sum-entropy Camera Assignment (MSCA), and Maximum Lifetime Scheduling (MLS). The MDHL problem aims to find the optimal locations to place the multimedia processing hubs, which operate on different channels for concurrently collecting images from adjacent cameras, such that the number of channels required for frequency reuse is minimized. With the locations of the hubs determined by the MDHL problem, the objective of the MSCA problem is to assign each camera to a hub in such a way that the global compression gain is maximized by jointly encoding the visually correlated images gathered by each hub. At last, given a hub and its associated cameras, the MLS problem targets at designing a schedule for the cameras such that the network lifetime of the cameras is maximized by letting highly correlated cameras perform differential coding on the fly. It is proven in this paper that the MDHL problem is NP-complete, and the others are NP-hard. Consequently, approximation and heuristic algorithms are proposed. Since the designed algorithms only take the camera settings as inputs, they are independent of specific multimedia applications. Experiments and simulations show that the proposed image gathering schemes effectively enhance network throughput and image compression performance.

In this paper, the effects of the primary-user (PU) mobility on spectrum sensing in Cognitive Radio (CR) networks are studied. To this aim, first, the spectrum sensing problem is reformulated to account for the PU mobility. Then, the effects of the PU mobility are studied with the objective to determine the parameters that affect the spectrum sensing functionality. For this, two performance metrics are analytically derived: i) the detection capability, which measures the PU mobility impact on the CR user detection probability; ii) the mobility-enabled sensing capacity, a new metric that measures the expected transmission capacity achievable by a CR user in the presence of PU mobility. The mathematical analysis is carried out in different scenarios, by using mobility and spectrum occupancy models. The results show that the detection capability is affected by five parameters: the PU protection range, the network region size, the PU mobility model, the CR spatial distribution, and the number of PUs that use the same spectrum band. Moreover, it is shown that the sensing capacity can significantly increase in the presence of PU mobility if the PU protection range is smaller than the network region size. The mathematical results are derived by considering the dynamic PU traffic, and validated through simulations.

Nanotechnology is enabling the development of sensing devices just a few hundreds of nanometers in size, which are able to measure new types of events in the nanoscale by exploiting the properties of novel nanomaterials. Wireless communication among these nanosensors will boost the range of applications of nanotechnology in the biomedical, environmental and military fields, amongst others. Within the different alternatives for communication in the nanoscale, recent advancements in nanomaterials point to the Terahertz band (0.1-10.0 THz) as the frequency range of operation of future electronic nano-devices. This still unlicensed band can theoretically support very large transmission bit-rates in the short range, i.e., for distances below one meter. More importantly, the Terahertz band also enables very simple communication mechanisms suited to the very limited capabilities of nanosensors. In this paper, a new communication paradigm called TS-OOK (Time Spread On-Off Keying) for Electromagnetic Wireless Nanosensor Networks (WNSNs) is presented. This new technique is based on the transmission of femtosecond-long pulses by following an on-off keying modulation spread in time. The performance of this scheme is assessed in terms of information capacity for the single-user case as well as aggregated network capacity for the multiuser case. The results show that by exploiting the peculiarities of the Terahertz band, this scheme provides a very simple but robust communication technique for WNSNs. Moreover, it is shown that, due to the peculiar behavior of the noise in the Terahertz band, the single-user capacity and the aggregated network capacity can exceed those of the AWGN channel classical wireless networks, when the appropriate channel codes are used.

Relay is one of the key features being considered for IMT-Advanced systems. The relay architectures defined in IEEE 802.16m and 3GPP LTE-Advanced are optimized only for non-mobile relay, i.e., the Relay Station is attached to a designated Base Station and becomes a part of the fixed access network. A mobile relay architecture, where relay may switch attached BS according to operation demand, will promise more resilient relay deployment. In this paper, we first highlight three use cases where mobile relays can offer useful deployment options. Next, we propose an enhanced handover mechanism for relay-based group mobility by extending the IEEE 802.16m specification on relay. To this end, we describe the handover architecture for mobile relay highlighting the C-plane and U-plane enhancements required in order to support group mobility of mobile stations. Using illustration and comparisons, we show that mobile relay will offer significant benefits of signaling overhead reduction and provide users seamless mobility experience compared to fixed relays.

Cognitive radio (CR) technology enables the opportunistic use of the vacant licensed frequency bands, thereby improving the spectrum utilization. However, the CR operation must not interfere with the transmissions of the licensed or primary users (PUs), and this is generally achieved by incurring a trade-off in the CR network performance. In order to evaluate this trade-off, a distributed CR routing protocol for ad hoc networks (CRP) is proposed that makes the following contributions: (i) explicit protection for PU receivers that are generally not detected during spectrum sensing, (ii) allowing multiple classes of routes based on service differentiation in CR networks, and (iii) scalable, joint route-spectrum selection. A key novelty of CRP is the mapping of spectrum selection metrics, and local PU interference observations to a packet forwarding delay over the control channel. This allows the route formation undertaken over a control channel to capture the environmental and spectrum information for all the intermediate nodes, thereby reducing the computational overhead at the destination. Results reveal the importance of formulating the routing problem from the viewpoint of safeguarding the PU communication, which is a unique feature in CR networks.

Cognitive radio (CR) technology allows devices to opportunistically use the vacant portions of the licensed wireless spectrum. However, the available spectrum changes dynamically with the primary user (PU) activity, necessitating frequent PU sensing coordination and exchanging network topology information in a multihop CR ad hoc network. To facilitate these tasks, an always-on, out-of-band common control channel (CCC) design is proposed that uses noncontiguous OFDM subcarriers placed within the guard bands separating the channels of the licensed spectrum. First, the task of choosing the OFDM-specific parameters, including the number, power, and bandwidth of the subcarriers is formulated as a feasibility problem to ensure that the CCC does not adversely interfere with the PU operation. Second, for unicast messaging between a given pair of users, a subset of the guard bands may be chosen, which allows an additional measure of protection for the adjacent PU spectrum. For this, the multiarm bandit algorithm is used that allows the guard band selection to evolve over time based on the observed interference from the PU. Results reveal that our proposed CCC ensures connectivity and improved PU protection with a limited trade-off in data rate when compared to frequency-hopping and cluster-based CCC schemes.

Cognitive radio networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face to a unique challenge based on the fluctuating nature of heterogeneous spectrum bands as well as the diverse service requirements of various applications. In this paper, a spectrum decision framework is proposed to determine a set of spectrum bands by considering the application requirements as well as the dynamic nature of spectrum bands. To this end, first, each spectrum is characterized by jointly considering primary user activity and spectrum sensing operations. Based on this, a minimum variance-based spectrum decision is proposed for real-time applications, which minimizes the capacity variance of the decided spectrum bands subject to the capacity constraints. For best-effort applications, a maximum capacity-based spectrum decision is proposed where spectrum bands are decided to maximize the total network capacity. Moreover, a dynamic resource management scheme is developed to coordinate the spectrum decision adaptively dependent on the time-varying cognitive radio network capacity. Simulation results show that the proposed methods provide efficient bandwidth utilization while satisfying service requirements.

Data redundancy caused by correlation has motivated the application of collaborative multimedia in-network processing for data filtering and compression in wireless multimedia sensor networks (WMSNs). This paper proposes an information theoretic image compression framework with an objective to maximize the overall compression of the visual information gathered in a WMSN. The novelty of this framework relies on its independence of specific image types and coding algorithms, thereby providing a generic mechanism for image compression under different coding solutions. The proposed framework consists of two components. First, an entropy-based divergence measure (EDM) scheme is proposed to predict the compression efficiency of performing joint coding on the images collected by spatially correlated cameras. The EDM only takes camera settings as inputs without requiring statistics of real images. Utilizing the predicted results from EDM, a distributed multi-cluster coding protocol (DMCP) is then proposed to construct a compression-oriented coding hierarchy. The DMCP aims to partition the entire network into a set of coding clusters such that the global coding gain is maximized. Moreover, in order to enhance decoding reliability at data sink, the DMCP also guarantees that each sensor camera is covered by at least two different coding clusters. Experiments on H.264 standards show that the proposed EDM can effectively predict the joint coding efficiency from multiple sources. Further simulations demonstrate that the proposed compression framework can reduce 10%–23% total coding rate compared with the individual coding scheme, i.e., each camera sensor compresses its own image independently.

In many recent studies on cognitive radio (CR) networks, the primary user activity is assumed to follow the Poisson traffic model with exponentially distributed interarrivals. The Poisson modeling may lead to cases where primary user activities are modeled as smooth and burst-free traffic. As a result, this may cause the cognitive radio users to miss some available but unutilized spectrum, leading to lower throughput and high false-alarm probabilities. The main contribution of this paper is to propose a novel model to parametrize the primary user traffic in a more efficient and accurate way in order to overcome the drawbacks of the Poisson modeling. The proposed model makes this possible by arranging the first-difference filtered and correlated primary user data into clusters. In this paper, a new metric called the Primary User Activity Index, , is introduced, which accounts for the relation between the cluster filter output and correlation statistics. The performance of the proposed model is evaluated by means of traffic estimation accuracy, false-alarm probabilities while keeping the detection probability of primary users at a constant value. Simulation results show that the appropriate selection of the Primary User Activity Index, higher primary-user detection accuracy, reduced false-alarm probabilities, and higher throughput can be achieved by the proposed model.

Recently, there has been a great deal of research on using mobility in wireless sensor networks (WSNs) to facilitate surveillance and reconnaissance in a wide deployment area. Besides providing an extended sensing coverage, node mobility along with spatial correlation introduces new network dynamics, which could lead to the traffic patterns fundamentally different from the traditional (Markovian) models. In this paper, a novel traffic modeling scheme for capturing these dynamics is proposed that takes into account the statistical patterns of node mobility and spatial correlation. The contributions made in this paper are twofold. First, it is shown that the joint effects of mobility and spatial correlation can lead to bursty traffic. More specifically, a high mobility variance and small spatial correlation can give rise to pseudo-long-range-dependent (LRD) traffic (high bursty traffic), whose autocorrelation function decays slowly and hyperbolically up to a certain cutoff time lag. Second, due to the ad hoc nature of WSNs, certain relay nodes may have several routes passing through them, necessitating local traffic aggregations. At these relay nodes, our model predicts that the aggregated traffic also exhibits the bursty behavior characterized by a scaled power-law decayed autocovariance function. According to these findings, a novel traffic shaping protocol using movement coordination is proposed to facilitate effective and efficient resource provisioning strategy. Finally, simulation results reveal a close agreement between the traffic pattern predicted by our theoretical model and the simulated transmissions from multiple independent sources, under specific bounds of the observation intervals

Nanotechnologies promise new solutions for several applications in the biomedical, industrial and military fields. At the nanoscale, a nanomachine is considered as the most basic functional unit which is able to perform very simple tasks. Communication among nanomachines will allow them to accomplish more complex functions in a distributed manner. In this paper, the state of the art in molecular electronics is reviewed to motivate the study of the Terahertz Band (0.1-10.0 THz) for electromagnetic (EM) communication among nano-devices. A new propagation model for EM communications in the Terahertz Band is developed based on radiative transfer theory and in light of molecular absorption. This model accounts for the total path loss and the molecular absorption noise that a wave in the Terahertz Band suffers when propagating over very short distances. Finally, the channel capacity of the Terahertz Band is investigated by using this model for different power allocation schemes, including a scheme based on the transmission of femtosecond-long pulses. The results show that for very short transmission distances, in the order of several tens of millimeters, the Terahertz channel supports very large bit-rates, up to few terabits per second, which enables a radically different communication paradigm for nanonetworks.

In underground tunnels with vehicular traffic flow, wireless communications experience severe fading problems due to the signal reflections and diffractions on the tunnel walls and the mobile vehicles. Currently, most of the existing tunnel channel models can only characterize the signal propagation in empty tunnels. Existing investigations on the influence of the vehicles are all limited to experimental or numerical results. This paper provides a theoretical analysis of the wireless channel in tunnels with vehicular traffic flow. First, the effects of a single vehicle on the signal propagation in a tunnel are investigated. The analytical expressions of the in-mode loss and the mode coupling coefficients are provided using the uniform theory of diffraction (UTD), Poisson summation formula, and the saddle point method. Then the channel model in a tunnel with either deterministic or random vehicular traffic flow is provided according to the analysis on a single vehicle's effect. The predicted received power given by our theoretical model has a good match with the numerical simulation results. Our channel model shows that the signal propagation in tunnels with vehicular traffic flow is influenced by multiple factors, including the number, the size and position of the vehicles, the size and the curvature of the tunnel, the vehicular traffic load, and the vehicle velocity.

In underground mine and road tunnels, multipath fading is much more severe than in the terrestrial wireless channels. To overcome the multipath fading in underground tunnels, MIMO (Multiple Input Multiple Output) and Cooperative Communication system can be utilized. Since the underground channel characteristics are significantly different from those in terrestrial environments, the channel capacity and the outage behavior of such systems need to be investigated based on underground tunnel channel models, which had not been addressed by the research community yet. In this paper, the capacity distribution and outage probability of MIMO and cooperative communication systems are investigated in underground tunnel environments. Explicit formulas of the capacity distribution and outage probability are developed as functions of environmental conditions and system configurations. Based on the capacity and outage analysis in underground tunnels, the optimal MIMO antenna geometry design scheme is proposed for MIMO systems; and the cooperative relay assignment protocol is developed for cooperative communication systems. Simulations are conducted to validate the theoretical results.

In wireless underground sensor networks (WUSNs), due to the dynamic underground channel characteristics and the heterogeneous network architecture, the connectivity analysis is much more complicated than in the terrestrial wireless sensor networks and ad hoc networks, which was not addressed before, to our knowledge. In this paper, a mathematical model is developed to analyze the dynamic connectivity in WUSNs, which captures the effects of the environmental parameters such as the soil composition and the soil moisture, and the system parameters such as the operating frequency, the sensor burial depth, the sink antenna height, the density of the sensor and sink devices, the tolerable latency of the networks, and the number and the mobility of the above-ground sinks. The lower and upper bounds of the connectivity probability are derived to analytically provide principles and guidelines for the design and deployment of WUSNs in various environmental conditions.

The spatial correlation among the images retrieved from distributed video sensors leads to considerable data redundancy, thus resulting in significant performance degradation in energy efficiency and QoS satisfaction. In this paper, a correlation-aware QoS routing algorithm (CAQR) is proposed to efficiently deliver visual information under QoS constraints by exploiting the correlation among video sensors. Firstly, a correlation-aware differential coding scheme is designed to reduce the amount of traffic generated by correlated video sensors. Then, a correlation-aware load balancing scheme is proposed to prevent network congestion by splitting the correlated flows that cannot be reduced to different paths. Finally, these correlation-aware schemes are integrated into an optimization QoS routing framework with an objective to minimize energy consumption subject to QoS constraints. Simulation results show that the proposed algorithm achieves efficient delivery of visual information under QoS constraints in wireless video sensor networks.

New propagation techniques using magnetic induction (MI) waveguide solve the problems of traditional techniques in the underground soil medium. However, the deployment of the MI waveguide to connect the wireless underground sensor networks (WUSNs) is challenging due to the high deployment cost and the complex shape of the communication range of the MI waveguides. In this paper, two algorithms are proposed to deploy the MI waveguides to connect the underground sensors in the WUSNs. To minimize the number of relay coils, the MST algorithm based on the minimum spanning tree is developed. However, the network constructed by the MST algorithm is not robust to sensor failures. To enhance the network robustness with acceptable relay coil number, the TC algorithm based on the Voronoi diagram is developed. The effectiveness of the proposed deployment algorithms is validated by simulations.

The ability of adapting to the environment in the most efficient way is a crucial issue in Cognitive Radio (CR) networks. For this purpose, an accurate estimation of the characteristics and activity of the Primary Users (PUs) is required. A system that takes into account heterogeneous PUs with several features is developed. A new scheme is integrated in the system to exploit these motleys and to improve the adaptability in CR networks. Through the proposed PU signal type recognition, the PU signal is detected and classified. The features of each PU type: the allowed interference levels, the bandwidth and the idle time, are extracted and exploited for CR adaptability effects. For this, a new CR throughput/interference adapter is proposed. The CR throughput is efficiently increased depending on the specific characteristics of PU types. Simulation results show that the proposed PU type recognition detects, distinguishes and classifies PU signals in Additive White Gaussian Noise (AWGN). It is shown that CR throughput varies with PU features for the improvement of CR adaptability.

Recently, there has been a great deal of research on investigating the effects of mobility on network attributes such as capacity, connectivity, and coverage. In this paper, the node mobility is studied from a new perspective with an objective to reveal the inherent impact of different mobility models on the the traffic patterns in wireless sensor networks. Specifically, the transmission pattern of a mobile sensor node is first characterized by an alternating renewal process that changes states between the active and the inactive. Then, the active state distribution is investigated under four commonly used mobility models: random walk, random waypoint, discrete Brownian motion, and extended Levy walk. For each mobility model, the spectrum of the traffic oriented from a single node is analyzed based on renewal theory. According to this analysis, novel results regarding the impact of each mobility model on the traffic nature are found: random walk, random waypoint, and discrete Brownian motion can only induce short range dependent traffic, whose autocorrelation function decays exponentially fast. In contrast, the traffic under extended Levy walk exhibits pseudo long range dependence, in which the autocorrelation function decays slower than exponential and follows a power law form at large time lags. Finally, the revealed findings are verified by the statistical analysis on the collected traffic traces from the simulated transmissions.

We investigate the dynamic connectivity of cognitive radio ad-hoc networks (secondary networks) coexisting with licensed networks (primary networks) that experience time-varying on-off links. It is shown that there exists a critical density λs*such that if the density of secondary networks is larger than λs*, the secondary network percolates at all time t >; 0, i.e., there exists always an infinite connected component in the secondary network under the time- varying spectrum availability. Furthermore, the upper and lower bounds of λs*are derived and it is shown that they do not depend on the random locations of primary and secondary users, but only on the network parameters, such as active/inactive probability of primary users, transmission range, and the user density.

Nanotechnology is enabling the development of devices in a scale ranging from one to a few hundred nanometers. Coordination and information sharing among these nano-devices will lead towards the development of future nanonetworks, rising new applications of nanotechnology in the medical, environmental and military fields. Despite the major progress in nano-device design and fabrication, it is still not clear how these atomically precise machines will communicate. The latest advancements in graphene- based electronics have opened the door to electromagnetic communication among nano-devices in the terahertz band (0.1-10 THz). This frequency band can potentially provide very large bandwidths, ranging from the entire band to several gigahertz- wide windows, depending on the transmission distance and the molecular composition of the channel. In this paper, the capacity of the terahertz channel is numerically evaluated by using a new terahertz propagation model, for different channel molecular compositions, and under different power allocation schemes. A novel communication technique based on the transmission of ultra-short pulses, less than one picosecond long, is motivated and quantitatively compared to the capacity- optimal power allocation scheme. The results show that for the very short range, up to a few tens of millimeters, the transmission of short pulses offer a realistic and still efficient way to exploit the terahertz channel.

It is well known that the electromagnetic (EM) waves do not propagate well in road tunnels. The channel characteristics for empty tunnels have already been well analyzed by both theoretical and numerical/experimental methods. However, any road tunnels are full with running vehicles. Currently a few works have investigated the influence of the vehicles on the signal propagation in road tunnels. However, they are all limited to experimental or numerical results. This paper provides a theoretical mode-based analysis to give the straightforward description of the wireless channel in road tunnels with traffic flow. First the effects of a single vehicle in the tunnel are investigated. The analytical expressions of the in-mode loss and the mode coupling are provided using uniform theory of diffraction (UTD), Poisson summation formula and saddle point method. Then the channel model for a L-lane road tunnel with the Poisson traffic flow is provided basing on the analysis on single vehicle's effect.

Data redundancy caused by correlation has motivated the application of collaborative multimedia in-network processing for data filtering and compression in wireless multimedia sensor networks (WMSNs). This paper proposes an information theoretic data compression framework with an objective to maximize the overall compression of the visual information gathered in a WMSN. To achieve this, an entropy-based divergence measure (EDM) scheme is proposed to predict the compression efficiency of performing joint coding on the images collected by spatially correlated cameras. The novelty of EDM relies on its independence of the specific image types and coding algorithms, thereby providing a generic mechanism for prior evaluation of compression under different coding solutions. Utilizing the predicted results from EDM, a distributed multi-cluster coding protocol (DMCP) is proposed to construct a compression-oriented coding hierarchy. The DMCP aims to partition the entire network into a set of coding clusters such that the global coding gain is maximized. Moreover, in order to enhance decoding reliability at data sink, the DMCP also guarantees that each sensor camera is covered by at least two different coding clusters. Experiments on H.264 standards show that the proposed EDM can effectively predict the joint coding efficiency from multiple sources. Further simulations demonstrate that the proposed compression framework can reduce 10% - 23% total coding rate compared with the individual coding scheme, i.e., each camera sensor compresses its own image independently.

Nanotechnology is enabling the development of devices in a scale ranging from one to a few one hundred nanometers. Nanonetworks, i.e., the interconnection of nano-scale devices, are expected to expand the capabilities of single nano-machines by allowing them to cooperate and share information. Traditional communication technologies are not directly suitable for nanonetworks mainly due to the size and power consumption of existing transmitters, receivers and additional processing components. All these define a new communication paradigm that demands novel solutions such as nano-transceivers, channel models for the nano-scale, and protocols and architectures for nanonetworks. In this talk, first the state-of-the-art in nano-machines, including architectural aspects, expected features of future nano-machines, and current developments are presented for a better understanding of the nanonetwork scenarios. Moreover, nanonetworks features and components are explained and compared with traditional communication networks. Novel nano-antennas based on nano-materials as well as the terahertz band are investigated for electromagnetic communication in nanonetworks. Furthermore, molecular communication mechanisms are presented for short-range networking based on ion signaling and molecular motors, for medium-range networking based on flagellated bacteria and nanorods, as well as for long-range networking based on pheromones and capillaries. Finally, open research challenges such as the development of network components, molecular communication theory, and new architectures and protocols, which need to be solved in order to pave the way for the development and deployment of nanonetworks within the next couple of decades are presented.

The growing problem of spectrum scarcity and the inefficient spectrum utilization in the licensed bands, are addressed by the emerging Cognitive Radio (CR) paradigm. It is seen that the choice of the spectrum bands, called as spectrum decision, must be organized carefully by considering the challenges in the spectrum availability over time, the short term fluctuations in the availability, and the heterogeneous Quality of Service (QoS) requirements of the cognitive radio users. Taking into account these challenges, the main contribution of this paper is to design a QoS-aware spectrum decision framework that achieves higher throughput and fairness in CR networks. The available spectrum fluctuations are characterized by using queueing theoretic models and are parametrized by a novel QoS parameter called opportunity index, Ψ. The heterogeneous QoS requirements of CR users are classified by defining another novel QoS parameter called request index, κ. An admission control algorithm is designed to stabilize the heterogeneous QoS requirements according to Ψ and κ. A spectrum decision algorithm is developed to select most appropriate spectrum bands considering the stabilized QoS requirements and the characterized spectrum. Moreover, by using a novel spectrum mobility algorithm the available spectrum is continuously monitored for dynamic variations in the CR network. The simulations demonstrate that our QoS-aware spectrum characterization and decision framework maximizes the total throughput while maintaining the fairness.

In cognitive radio networks, spectrum sensing is a fundamental function for detecting the presence of primary users in licensed frequency bands. Due to multipath fading and shadowing, the performance of detection may be considerably compromised. To improve the detection probability, cooperative sensing is an effective approach for secondary users to cooperate and combat channel impairments. This approach, however, incurs overhead such as sensing delay for reporting local decisions and the increase of control traffic in the network. In this paper, a reinforcement learning-based cooperative sensing method is proposed to address the cooperation overhead problem. By using the proposed cooperative sensing model, the secondary user learns to (i) find the optimal set of cooperating neighbors with minimum control traffic, (ii) minimize the overall cooperative sensing delay, (iii) select independent users for cooperation under correlated shadowing, and (iv) improve the energy efficiency for cooperative sensing. The simulation results show that the proposed reinforcement learning-based cooperative sensing method reduces the overhead of cooperative sensing while effectively improving the detection performance to combat correlated shadowing.

This paper investigates the probabilistic connectivity of the Wireless Underground Sensor Networks (WUSNs). Due to the unique channel characteristics and the heterogeneous network architecture of the WUSNs, the connectivity analysis is much more complicated than in the terrestrial wireless sensor networks and ad hoc networks. To our knowledge, this connectivity problem in WUSNs was not addressed before. In this paper, a mathematical model is developed to analyze the probabilistic connectivity in WUSNs, which captures the effects of environmental parameters such as the soil moisture and soil composition, and system parameters such as the operating frequency, the sensor burial depth, the sink antenna height, the density of the sensor devices, the tolerable latency of the networks, and the number and the mobility of the above- ground sinks. The lower and upper bounds for the connectivity probability are derived analytically. Simulation studies are performed, where the theoretical bounds are validated, and the effects of several environmental and system parameters on the performance of these networks are investigated.

Molecular communication has been recently proposed for interconnected nano-scale devices as an alternative to classical communication paradigms such as electromagnetic waves, acoustic or optical communication. In this novel approach, the information is encoded as molecules that are transported between nano-scale devices within different distances. For short distances (nm-mm ranges) there exist molecular motors and calcium signaling techniques to realize the communication. For long distances (mm-m ranges), pheromones are used to transport information. In this work, the medium-range is explored to cover distances from ¿m to mm and a molecular network architecture is proposed to realize the communication between nano-machines that can be deployed over different (short, medium and long) distances. In addition, two new communication techniques, flagellated bacteria and catalytic nanomotors, are proposed to cover the medium-range. Both techniques are based on the transport of DNA encoded information between emitters and receivers by means of a physical carrier. Finally, a qualitative comparison of both communication techniques is carried out and some future research topics are pointed out.

Wireless Multimedia Sensor Networks (WMSNs) are distributed systems of wirelessly networked devices that allow retrieving video and audio streams, still images, and scalar sensor data. WMSNs will be a crucial component of mission-critical networks to protect the operation of strategic national infrastructure, provide support to counteract emergencies and threats, and enhance infrastructure for tactical military operations. To enable these applications, WMSNs require the sensor network paradigm to be re-thought in view of the need for mechanisms to deliver multimedia content with a pre-defined level of quality of service (QoS). In this paper, a new cross-layer communication architecture based on the time-hopping impulse radio ultra wide band technology is described, whose objective is to reliably and flexibly deliver QoS to heterogeneous applications in WMSNs, by leveraging and controlling interactions among different layers of the protocol stack according to applications requirements. Simulations show that the proposed system achieves the performance objectives of WMSNs without sacrificing on the modularity of the overall design.

Molecular communication is a promising paradigm for nanoscale networks. The end-to-end (including the channel) models developed for classical wireless communication networks need to undergo a profound revision so that they can be applied for nanonetworks. Consequently, there is a need to develop new end-to-end (including the channel) models which can give new insights into the design of these nanoscale networks. The objective of this paper is to introduce a new physical end-to-end (including the channel) model for molecular communication. The new model is investigated by means of three modules, i.e., the transmitter, the signal propagation and the receiver. Each module is related to a specific process involving particle exchanges, namely, particle emission, particle diffusion and particle reception. The particle emission process involves the increase or decrease of the particle concentration rate in the environment according to a modulating input signal. The particle diffusion provides the propagation of particles from the transmitter to the receiver by means of the physics laws underlying particle diffusion in the space. The particle reception process is identified by the sensing of the particle concentration value at the receiver location. Numerical results are provided for three modules, as well as for the overall end-to-end model, in terms of normalized gain and delay as functions of the input frequency and of the transmission range.

Wireless networks can greatly facilitate the communication in underground mines and road/subway tunnels, where the propagation characteristics of electromagnetic (EM) waves are significantly different from those in terrestrial environments. According to the structure of underground mines and road tunnels, two types of channel models can be utilized, namely, tunnel and room/pillar channel models. However, there exists no theoretical model for room-and-pillar channel in underground mines to date, and current existing tunnel channel models do not provide an analytical solution for both near and far regions of the sources. In this paper, the multimode model is proposed, which provides an analytical expression for the received power and the power delay profile at any position in a tunnel.Moreover, the multimode model is extended to characterize the room-and-pillar channel in the underground mines after combining it with the shadow fading model. The theoretical models are validated by experimental measurements. Based on the proposed channel models, the effects of various factors on the signal propagation are analyzed. The factors include: the operating frequency, the size of the tunnel or underground mine room, the antenna position and polarization, and the electrical parameters.

In Wireless Sensor and Actor Networks (WSANs), the collaborative operation of sensors enables the distributed sensing of a physical phenomenon, while actors collect and process sensor data and perform appropriate actions. WSANs can be thought of as a distributed control system that needs to timely react to sensor information with an effective action. In this paper, coordination and communication problems in WSANs with mobile actors are studied. First, a new location management scheme is proposed to handle the mobility of actors with minimal energy expenditure for the sensors, based on a hybrid strategy that includes location updating and location prediction. Actors broadcast location updates limiting their scope based on Voronoi diagrams, while sensors predict the movement of actors based on Kalman filtering of previously received updates. The location management scheme enables efficient geographical routing, and based on this, an optimal energy-aware forwarding rule is derived for sensor-actor communication. Consequently, algorithms are proposed that allow controlling the delay of the data-delivery process based on power control, and deal with network congestion by forcing multiple actors to be recipients for traffic generated in the event area. Finally, a model is proposed to optimally assign tasks to actors and control their motion in a coordinated way to accomplish the tasks based on the characteristics of the events. Performance evaluation shows the effectiveness of the proposed solution.

Severe energy constraints of battery-powered sensor nodes necessitate energy-efficient communication in Wireless Sensor Networks (WSNs). However, the vast majority of the existing solutions are based on the classical layered protocol approach, which leads to significant overhead. It is much more efficient to have a unified scheme, which blends common protocol layer functionalities into a cross-layer module. In this paper, a cross-layer protocol (XLP) is introduced, which achieves congestion control, routing, and medium access control in a cross-layer fashion. The design principle of XLP is based on the cross-layer concept of initiative determination, which enables receiver-based contention, initiative-based forwarding, local congestion control, and distributed duty cycle operation to realize efficient and reliable communication in WSNs. The initiative determination requires simple comparisons against thresholds, and thus, is very simple to implement, even on computationally constrained devices. To the best of our knowledge, XLP is the first protocol that integrates functionalities of all layers from PHY to transport into a cross-layer protocol. A cross-layer analytical framework is developed to investigate the performance of the XLP. Moreover, in a cross-layer simulation platform, the state-of-the-art layered and cross-layer protocols have been implemented along with XLP for performance evaluations. XLP significantly improves the communication performance and outperforms the traditional layered protocol architectures in terms of both network performance and implementation complexity.

Underwater multimedia acoustic sensor networks will enable new underwater applications such as multimedia coastal and tactical surveillance, undersea explorations, picture and video acquisition and classification, and disaster prevention. Because of the different application requirements, there is a need to provide differentiated-service support to delay-sensitive and delay-tolerant data traffic as well as to loss-sensitive and loss-tolerant traffic. While research on underwater communication protocol design so far has followed the traditional layered approach originally developed for wired networks, improved performance can be obtained with a cross-layer design. Hence, the objective of this work is twofold: (1) study the interactions of key underwater communication functionalities such as modulation, forward error correction, medium access control, and routing; and (2) develop a distributed cross-layer communication solution that allows multiple devices to efficiently and fairly share the bandwidth-limited high-delay underwater acoustic medium.

Underwater Acoustic Sensor Networks (UW-ASNs) consist of devices with sensing, processing, and communication capabilities that are deployed underwater to perform collaborative monitoring tasks to support a broad range of applications. The enabling communication technology for distances over one hundred meters is wireless acoustic networking because of the high attenuation and scattering affecting radio and optical waves, respectively. In this work, the problem of data gathering is investigated by considering the interactions between the routing functions and the characteristics of the underwater acoustic channel. Two distributed geographical routing algorithms for delay-insensitive and delay-sensitive applications are proposed and shown through simulation experiments to meet the application requirements.

The MIMO (Multiple Input Multiple Output) systems can efficiently mitigate the severe multipath fading effects in underground tunnels. Due to the unique tunnel channel characteristics, there exist optimal antenna geometries that can maximize the MIMO channel capacity. In this paper, an optimal MIMO antenna geometry design scheme is developed based on the analysis of the channel capacity in underground tunnels. The MIMO channel capacities in both empty tunnels and tunnels with obstructions are analytically expressed to facilitate the antenna geometry design. Simulation results show that the MIMO system with designed antenna geometry has obvious improvements in channel capacity than the system with the traditional linear array antenna geometry.

Recently there has been a great deal of research on using mobility in wireless sensor networks to facilitate surveillance and reconnaissance in a wide deployment area. Besides providing an extended sensing coverage, the node mobility along with the spatial correlation of the monitored phenomenon introduces new dynamics to the network traffic. These dynamics could lead to long range dependent (LRD) traffic, which necessitates network protocols fundamentally different from what we have employed in the traditional (Markovian) traffic. Therefore, characterizing the effects of mobility and spatial correlation on the dynamic behavior of the network traffic is particularly important in the effective design of network protocols. In this paper, a novel traffic modeling scheme for capturing these dynamics is proposed that takes into account the statistical patterns of human mobility and spatial correlation. The contributions made in this paper are twofold: first, it is shown that the mobility variability and the spatial correlation can lead to the pseudo-LRD traffic, whose autocorrelation function follows a power law form with the Hurst parameter up to a certain cutoff time lag. Second, it is shown that the degree of traffic burstiness, which is characterized by the Hurst parameter, has an intimate connection with the mobility variability and the degree of spatial correlation. Furthermore, we show that this connection can be utilized to design the mobility-aware traffic smoothing schemes, which point out a new direction for traffic control protocols. Finally, simulation results reveal a close agreement between the traffic pattern predicted by our theoretical model and the simulated transmissions from multiple independent sources, under specific bounds of the observation intervals.

Wireless sensor networks (WSNs) are being increasingly deployed in office blocks or residential areas for commercial applications, such as home automation, meter reading, surveillance, among others. At these locations, the WSNs experience interference in the 2.4 GHz unlicensed band due to wireless LANs (WLANs) and commercial microwave devices, leading up to 92% packet losses. In this paper, an algorithmic framework is proposed, that allows the sensor nodes to identify the type of the interferer and its operational channel, so that the former may adapt their own transmission to reduce packet losses in the network. Our proposed interference classification approach comprises of an (i) offline measurement of the spectral characteristics of the WLAN and microwave devices to obtain a reference spectrum shape, and (ii) matching the observed spectral pattern during network operation with the stored reference shape The knowledge of the interferer characteristics is then leveraged by the sensor nodes to decide their transmission channel, packet scheduling times and sleep-awake cycles. Results reveal that our approach incurs up to 50 - 70% energy savings in the WSN, by reducing interference related packet losses.

Wireless multimedia sensor networks (WMSNs) are interconnected devices that allow retrieving video and audio streams, still images, and scalar data from the environment. In a densely deployed WMSN, there exists correlation among the visual information observed by cameras with overlapped field of views. In this paper, the correlation characteristics of visual information are used to address two issues: 1) how to measure the amount of visual information provided by multiple cameras in the network, and 2) how to select a group of cameras to report their information to the sink under distortion constraints. An entropy-based analytical framework is developed to measure the amount of visual information provided by multiple correlated cameras first. Based on this framework, a correlation-based camera selection scheme is introduced. Simulation results show that, given a distortion bound at the sink, the correlation-based selection scheme requires fewer cameras to report to the sink than the random selection scheme.

Underground is a challenging environment for wireless communication since the propagation medium is no longer air but soil, rock and water. The well established wireless communication techniques using electromagnetic (EM) waves do not work well in this environment due to three problems: high path loss, dynamic channel condition and large antenna size. New techniques using magnetic induction (MI) can solve two of the three problems (dynamic channel condition and large antenna size), but may still cause even higher path loss. In this paper, a complete characterization of the underground MI communication channel is provided. Based on the channel model, the MI waveguide technique for communication is developed in order to reduce the MI path loss. The performance of the traditional EM wave systems, the current MI systems and our improved MI waveguide system are quantitatively compared. The results reveal that our MI waveguide system has much lower path loss than the other two cases for any channel conditions.

Existing research in transport protocols for wireless ad-hoc networks has focused on reliable end-to-end packet delivery under uncertain channel conditions, route failures due to node mobility and link congestion. In a cognitive radio (CR) environment, there are several key challenges that must be addressed apart from the above concerns. The intermittent spectrum sensing undertaken by the CR users, the activity of the licensed users of the spectrum, large-scale bandwidth variation based on spectrum availability, and the channel switching process need to be considered in the transport protocol design. In this paper, a window-based transport protocol for CR ad-hoc networks, TP-CRAHN, is proposed that distinguishes each of these events by a combination of explicit feedback from the intermediate nodes and the destination. This is achieved by adapting the classical TCP rate control algorithm running at the source to closely interact with the physical layer channel information, the link layer functions of spectrum sensing and buffer management, and a predictive mobility framework that is developed at the network layer. To the best of our knowledge, this is the first work on the transport layer to specifically address the concerns of the CR ad-hoc networks and our approach is thoroughly validated by simulation experiments.

Wireless multimedia sensor networks (WMSNs) are interconnected devices that allow retrieving video and audio streams, still images, and scalar data from the environment. In a densely deployed WMSN, there exists correlation among the visual information observed by cameras with overlapped field of views. This paper proposes a novel spatial correlation model for visual information in WMSNs. By studying the sensing model and deployments of cameras, a spatial correlation function is derived to describe the correlation characteristics of visual information observed by cameras with overlapped field of views. The joint effect of multiple correlated cameras is also studied. An entropy-based analytical framework is developed to measure the amount of visual information provided by multiple cameras in the network. Furthermore, according to the proposed correlation function and entropy-based framework, a correlation-based camera selection algorithm is designed. Experimental results show that the proposed spatial correlation function can model the correlation characteristics of visual information in WMSNs through low computation and communication costs. Further simulations show that, given a distortion bound at the sink, the correlation-based camera selection algorithm requires fewer cameras to report to the sink than the random selection algorithm.

UnderWater Acoustic Sensor Networks (UW-ASNs) consist of sensors and Autonomous Underwater Vehicles (AUVs) performing collaborative monitoring tasks. In this article, UWMAC, a distributed Medium Access Control (MAC) protocol designed for UW-ASNs, is introduced. The proposed MAC protocol is a transmitter-based Code Division Multiple Access (CDMA) scheme that incorporates a novel closed-loop distributed algorithm to jointly set the optimal transmit power and code length. CDMA is the most promising physical layer and multiple access technique for UW-ASNs because it is robust to frequency-selective fading, it compensates for the effect of multipath at the receiver, and it allows receivers to distinguish among signals simultaneously transmitted by multiple devices. UW-MAC aims at achieving three objectives, i.e., guarantee i) high network throughput, ii) low channel access delay, and iii) low energy consumption. It is demonstrated that UW-MAC simultaneously achieves these three objectives in deep water communications (where the ocean depth is more than 100 m), which are usually not severely affected by multipath. In shallow water communications, which may be heavily affected by multipath, it dynamically finds the optimal trade-off among these objectives according to the application requirements. UW-MAC is the first protocol that leverages CDMA properties to achieve multiple access to the scarce underwater bandwidth, while other protocols tailored for this environment have considered CDMA merely from a physical layer perspective. Experiments show that UW-MAC outperforms many existing MAC protocols tuned for the underwater environment under different architecture scenarios and simulation settings.

A cross-layer communication protocol called VSN-module is introduced for wireless video sensor networks based on ultrawideband (UWB) radio technology at the physical layer. The core of our solution is a distributed path reservation scheme which routes video traffic from sources (sensors) to a sink. The path establishment takes into account the specific requirements of video flows such as bandwidth, end-to-end delay and jitter, as well as the current status of the traversed devices such as the available bandwidth, the energy consumption, and the quality of the wireless channels. Simulation experiments are carried out and the performance of the VSN-module is evaluated in terms of maximum end-to-end delivery delay, maximum delay jitter, and power consumption, under different video flow requirements.

The propagation characteristics of electromagnetic (EM) waves in tunnels are significantly different from those in terrestrial environment. However, the current tunnel channel models cannot provide an analytical solution for both near and far region of the sources. In this paper, the Multimode model is proposed to completely characterize the wireless channel of tunnels in roads/subways as well as underground mines. The new model provides an analytical expression for the path loss and delay spread at any position in a tunnel. This theoretical model is validated by comparing results with experiment measurements. Our channel model reveals that: the mode attenuation is mostly determined by the tunnel size and operating frequency, while the mode intensity is governed by the position of the transmission antenna. Physical factors, such as, humidity, pressure and temperature of the tunnel air, as well as the material of tunnel walls have little influence on the signal propagation in tunnels.

A unique challenge for routing in cognitive radio networks is the collaboration between the route selection and spectrum decision. To solve this problem, in this paper a Spectrum-Tree base On-Demand routing protocol (STOD-RP) is proposed where a spectrum-tree is built in each spectrum band. The formation of the spectrum-tree addresses the cooperation between spectrum decision and route selection in an efficient way. In addition, a new route metric is proposed as well as a fast and efficient spectrum-adaptive route recovery method. Simulation results show that our proposed STOD-RP reduces the control overhead and shortens the average end-to-end delay significantly.

Wireless multimedia sensor networks (WMSNs) are networks of wirelessly interconnected devices that allow retrieving video and audio streams, still images, and scalar sensor data. WMSN require the sensor network paradigm to be rethought in view of the need for mechanisms to deliver multimedia content with a pre-defined level of quality of service (QoS). In this paper, a new cross-layer communication architecture based on the time-hopping impulse radio ultra wide band technology is described, designed to reliably and flexibly deliver QoS to heterogeneous applications in WMSNs, by leveraging and controlling interactions among different layers of the protocol stack according to applications requirements. Simulations show that the proposed system achieves the performance objectives of WMSNs without sacrificing on design modularity.

In this paper, a cross-layer solution for packet size optimization in wireless sensor networks (WSN) is introduced such that the effects of multi-hop routing, the broadcast nature of the physical wireless channel, and the effects of error control techniques are captured. A key result of this paper is that contrary to the conventional wireless networks, in wireless sensor networks, longer packets reduce the collision probability. Consequently, an optimization solution is formalized by using three different objective functions, i.e., packet throughput, energy consumption, and resource utilization. Furthermore, the effects of end-to-end latency and reliability constraints are investigated that may be required by a particular application. As a result, a generic, cross-layer optimization framework is developed to determine the optimal packet size in WSN. This framework is further extended to determine the optimal packet size in underwater and underground sensor networks. From this framework, the optimal packet sizes under various network parameters are determined.

Underwater multimedia acoustic sensor networks will enable new underwater applications such as multimedia coastal and tactical surveillance, undersea explorations, picture and video acquisition and classification, and disaster prevention. Because of the different requirements of these applications, it is needed to provide efficient differentiated-service support to delay-sensitive and delay-tolerant data traffic as well as to loss-sensitive and loss-tolerant traffic. The objective of this paper is twofold: 1) explore the interactions of different underwater communication functionalities such as modulation, forward error correction, medium access control and routing, and 2) develop a distributed cross-layer solution integrating specialized communication functionalities that cooperate to allow multiple devices to efficiently and fairly share the bandwidth-limited high-delay underwater acoustic medium.

Today's wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a high variance in time. The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. This new networking paradigm is referred to as cognitive radio networks. In this talk, the novel functionalities and current research challenges of the cognitive radio networks are explained in detail. More specifically, an overview of the cognitive radio technology is provided and the network architecture is introduced. Moreover, the cognitive network functions such as spectrum management, spectrum mobility and spectrum sharing are explained in detail. The influence of these functions on the performance of the upper layer protocols such as routing and transport are investigated. Moreover, the network management, operation and maintenance problems are highlighted and open research issues in these areas are also outlined.

Today’s wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a high variance in time. The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. This new networking paradigm is referred to as cognitive radio networks. In this talk, the novel functionalities and current research challenges of the cognitive radio networks are explained in detail. More specifically, an overview of the cognitive radio technology is provided and the network architecture is introduced. Moreover, the cognitive network functions such as spectrum management, spectrum mobility and spectrum sharing are explained in detail. The influence of these functions on the performance of the upper layer protocols such as routing and transport are investigated. Moreover, the network management, operation and maintenance problems are highlighted and open research issues in these areas are also outlined.

Today's wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a high variance in time. The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. This new networking paradigm is referred to as cognitive radio networks. In this talk, the novel functionalities and current research challenges of the cognitive radio networks are explained in detail. More specifically, an overview of the cognitive radio technology is provided and the network architecture is introduced. Moreover, the cognitive network functions such as spectrum management, spectrum mobility and spectrum sharing are explained in detail. The influence of these functions on the performance of the upper layer protocols such as routing and transport are investigated. Moreover, the network management, operation and maintenance problems are highlighted and open research issues in these areas are also outlined.

Wireless Mesh Networks (WMNs) are envisaged to extend Internet access and other networking services in personal, local, campus, and metropolitan areas. Mesh routers (MR) form the connectivity backbone while performing the dual tasks of packet forwarding as well as providing network access to the mesh clients. However, the performance of such networks is limited by traffic congestion, as only limited bandwidth is available for supporting the large number of nodes in close proximity. This problem can be alleviated by the cognitive radio paradigm that aims at devising spectrum sensing and management techniques, thereby allowing radios to intelligently locate and use frequencies other than those in the 2.4 GHz ISM band. These promising technologies are integrated in our proposed Cognitive Mesh NETwork (COMNET) algorithmic framework, thus realizing an intelligent frequency-shifting self-managed mesh network. The contribution of this paper is threefold: (1) A new approach for spectrum sensing is devised without any change to the working of existing de facto mesh protocols. (2) An analytical model is proposed that allows MRs to estimate the power in a given channel and location due to neighboring wireless LAN traffic, thus creating a virtual map in space and frequency domains. (3) These models are used to formulate the task of channel assignment within the mesh network as an optimization problem, which is solved in a decentralized manner. Our analytical models are validated through simulation study, and results reveal the benefits of load sharing by adopting unused frequencies for WMN traffic.

The availability of low-cost hardware is enabling the development of wireless multimedia sensor networks (WMSNs), i.e., networks of resource-constrained wireless devices that can retrieve multimedia content such as video and audio streams, still images, and scalar sensor data from the environment. In this paper, ongoing research onprototypesofmultimediasensorsand their integration intotestbedsforexperimentalevaluationof algorithms and protocols for WMSNs are described. Furthermore, open research issues and future research directions, both at the device level and at the testbed level, are discussed. This paper is intended to be a resource for researchers interested in advancing the state-of-the-art in experimental research on wireless multimedia sensor networks.

There exist several applications of sensor networks where the reliability of data delivery can be critical. Although the redundancy inherent in a sensor network might increase the degree of reliability, it by no means can provide any guaranteed reliability semantics. In this paper, we consider the problem of reliable sink-to-sensors data delivery. We first identify several fundamental challenges that need to be addressed and are unique to the environment of wireless sensor networks. We then propose a scalable framework for reliable downstream data delivery that is specifically designed to both address and leverage the characteristics of the wireless sensor networks while achieving the reliability in an efficient manner. Through ns2-based simulations, we evaluate the proposed framework.

Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Hence, recent research has been focused on the interference avoidance problem. Moreover, current radio frequency (RF) front-ends cannot perform sensing and transmission at the same time, which inevitably decreases their transmission opportunities, leading to the so-called sensing efficiency problem. In this paper, in order to solve both the interference avoidance and the spectrum efficiency problem, an optimal spectrum sensing framework is developed. More specifically, first a theoretical framework is developed to optimize the sensing parameters in such a way as to maximize the sensing efficiency subject to interference avoidance constraints. Second, in order to exploit multiple spectrum bands, spectrum selection and scheduling methods are proposed where the best spectrum bands for sensing are selected to maximize the sensing capacity. Finally, an adaptive and cooperative spectrum sensing method is proposed where the sensing parameters are optimized adaptively to the number of cooperating users. Simulation results show that the proposed sensing framework can achieve maximum sensing efficiency and opportunities in multi-user/multi-spectrum environments, satisfying interference constraints.

The focus of this paper is on wireless mesh networks. In particular, we study the multi-radio case, given the considerable improvement in network throughput that multiple radios allow to achieve and the availability of cost-effective wireless devices. Interesting research problems are still unsolved in this field. Due to the scarcity of non-overlapped frequency channels and available radios per node, interference is still present, which cuts the achievable throughput down. As interference depends on how channels are bound to radio interfaces, a proper channel assignment scheme is needed to reduce the interference. In this paper we identify some key requirements of a channel assignment scheme. Accordingly, a centralized channel assignment algorithm is developed for multi-radio wireless mesh networks in order to maximize the throughput and address the interference problems. Finally, a performance study is presented to assess the effectiveness of our proposed algorithm.

In wireless mesh networks, the end-to-end throughput of traffic flows depends on the path length, i.e. the higher the number of hops, the lower becomes the throughput. In this paper, a Fair End-to-end Bandwidth Allocation (FEBA) algorithm is introduced to solve this problem. FEBA is implemented at the Medium Access Control (MAC) layer of single-radio, multiple channels IEEE 802.16 mesh nodes, operated in a distributed coordinated scheduling mode. FEBA negotiates bandwidth among neighbors to assign a fair share to each end-to-end traffic flow. This is carried out in two steps. First, bandwidth is requested and granted in a round-robin fashion where heavily loaded links are provided with a proportionally higher amount of service than the lightly loaded links at each round. Second, at each output link, packets from different traffic flows are buffered in separate queues which are served by the Deficit Round Robin (DRR) scheduling algorithm. If multiple channels are available, all of them are shared evenly in order to increase the network capacity due to frequency reuse. The performance of FEBA is evaluated by extensive simulations and is shown to provide fairness by balancing the bandwidth among traffic flows.

In this paper, coordination and communication problems in wireless sensor and actor networks (WSANs) are jointly addressed in a unifying framework. A sensor-actor coordination model is proposed based on an event-driven partitioning paradigm. Sensors are partitioned into different sets, and each set is constituted by a data-delivery tree associated with a different actor. The optimal solution for the partitioning strategy is determined by mathematical programming, and a distributed solution is proposed. In addition, a new model for the actor-actor coordination problem is introduced. The actor coordination is formulated as a task assignment optimization problem for a class of coordination problems in which the area to be acted upon needs to be optimally split among different actors. An auction-based distributed solution of the problem is also presented. Performance evaluation shows how global network objectives, such as compliance with real-time constraints and minimum energy consumption, can be achieved in the proposed framework with simple interactions between sensors and actors that are suitable for large-scale networks of energy-constrained devices.

Mobility management protocols operating from different layers of the classical protocol stack (e.g., link, network, transport, and application layers) have been proposed in the last several years. These protocols achieve different handoff performance for different types of applications. In this paper, mobile applications are grouped into five different classes, class A through class E, based on their mobility management requirements. Analytical models are developed to investigate the handoff performance of the existing mobility management protocols for these application classes. The analysis shows that applications of a particular class experience different handoff performance when different mobility management protocols are used. Handoff performance comparisons of different mobility management protocols are carried out to decide on the suitable mobility management protocol for a particular application class. The results of mathematical analysis advocate the use of transport layer mobility management for class B and class C applications, mobile IP for non-real-time class D and class E applications, and session initiation protocol-based mobility management for real-time class D and class E applications. Moreover, through analytical modeling, the parameters that influence the handoff performance of mobility management protocols are identified. These parameters can be used to design new application-adaptive techniques to enhance the handoff performance of the existing mobility management protocols.

Underwater sensor networks consist of sensors and vehicles deployed to perform collaborative monitoring tasks over a given region. Underwater sensor networks will find applications in oceano-graphic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, tactical surveillance, and mine reconnaissance. Underwater acoustic networking is the enabling technology for these applications. In this paper, an architecture for three-dimensional underwater sensor networks is considered, and a model characterizing the acoustic channel utilization efficiency is introduced, which allows investigating some fundamental characteristics of the underwater environment. In particular, the model allows setting the optimal packet size for underwater communications given monitored volume, density of the sensor network, and application requirements. Moreover, the problem of data gathering is investigated at the network layer by considering the cross-layer interactions between the routing functions and the characteristics of the underwater acoustic channel. Two distributed routing algorithms are introduced for delay-insensitive and delay-sensitive applications. The proposed solutions allow each node to select its next hop, with the objective of minimizing the energy consumption taking the varying condition of the underwater channel and the different application requirements into account. The proposed routing solutions are shown to achieve the performance targets by means of simulation.

In wireless sensor and actor networks (WSANs), the collaborative operation of sensors enables the distributed sensing of a physical phenomenon, while actors collect and process sensor data and perform appropriate actions. In this paper, the coordination and communication problems in WSANs with mobile actors are studied. A hybrid location management scheme is introduced to handle the mobility of actors with minimal energy expenditure. Actors broadcast location updates limiting their scope based on Voronoi diagrams, whereas sensors predict the movement of actors based on Kalman filtering of previously received updates. An optimal energy-aware forwarding rule is then derived for sensor-actor communication, based on geographical routing. The proposed scheme allows controlling the delay of the data-delivery process based on power control, and deals with network congestion by forcing multiple actors to be recipients for traffic generated in the event area. The motion of actors is coordinated to optimally accomplish the tasks based on the characteristics of the events

Severe energy constraints and hence the low power communication requirements amplify the significance of the energy efficient and preferably cross-layer error control mechanisms in wireless sensor networks (WSN). In this paper, a cross-layer methodology for the analysis of error control schemes in WSNs is presented such that the effects of multi-hop routing and the broadcast nature of the wireless channel are investigated. More specifically, the cross-layer effects of routing, medium access and physical layers are considered. This analysis enables a comprehensive comparison of forward error correction (FEC) and automatic repeat request (ARQ) in WSNs. FEC schemes improve the error resiliency compared to ARQ. In a multi-hop network, this improvement can be exploited by reducing the transmit power (transmit power control) or by constructing longer hops (hop length extension), which can be achieved through channel-aware routing protocols. The results of our analysis reveal that for certain FEC codes, the hop length extension decreases both the energy consumption and the end-to-end latency subject to a target PER compared to ARQ. Thus, FEC codes can be regarded as an important candidate for delay sensitive traffic in WSNs. On the other hand, transmit power control results in significant savings in energy consumption at the cost of increased latency. Moreover, the cases where ARQ outperforms FEC codes are indicated for various end-to-end distance and target PER values

Next-generation wireless systems (NGWS) integrate different wireless networks, each of which is optimized for some specific services and coverage area to provide ubiquitous communications to the mobile users. It is an important and challenging issue to support seamless handoff management in this integrated architecture. The existing handoff management protocols are not sufficient to guarantee handoff support that is transparent to the applications in NGWS. In this work, a cross-layer (layer 2 + 3) handoff management protocol, CHMP, is developed to support seamless intra and intersystem handoff management in NGWS. Cross-layer handoff management protocol uses mobile's speed and handoff signaling delay information to enhance the handoff performance of mobile IP that is proposed to support mobility management in wireless IP networks. First, the handoff performance of mobile IP is analyzed with respect to its sensitivity to the link layer (layer 2) and network layer (layer 3) parameters. Then, a cross-layer handoff management architecture is developed using the insights learnt from the analysis. Based on this architecture, the detailed design of CHMP is carried out. Finally, extensive simulation experiments are carried out to evaluate the performance of CHMP. The theoretical analysis and simulation results show that CHMP significantly enhances the performance of both intra and intersystem handoffs

Wireless Sensor and Actor Networks (WSANs) are composed of a large number of heterogeneous nodes called sensors and actors. The collaborative operation of sensors enables the distributed sensing of a physical phenomenon, while the role of actors is to collect and process sensor data and perform appropriate actions.In this paper, a coordination framework for WSANs is addressed. A new sensor-actor coordination model is proposed, based on an event-driven clustering paradigm in which cluster formation is triggered by an event so that clusters are created on-the-fly to optimally react to the event itself and provide the required reliability with minimum energy expenditure. The optimal solution is determined by mathematical programming and a distributed solution is also proposed. In addition, a new model for actor-actor coordination is introduced for a class of coordination problems in which the area to be acted upon is optimally split among different actors. An auction-based distributed solution of the problem is also presented.Performance evaluation shows how global network objectives, such as compliance with real-time constraints and minimum energy consumption, can be reached in the proposed framework with simple interactions between sensors and actors that are suitable for large-scale networks of energy-constrained devices.

No abstract available.

Since ad hoc and sensor networks can be composed of a very large number of devices, the scalability of network protocols is a major design concern. Furthermore, network protocols must be designed to prolong the battery lifetime of the devices. However, most existing routing techniques for ad hoc networks are known not to scale well. On the other hand, the so-called geographical routing algorithms are known to be scalable but their energy efficiency has never been extensively and comparatively studied. In a geographical routing algorithm, data packets are forwarded by a node to its neighbor based on their respective positions. The neighborhood of each node is constituted by the nodes that lie within a certain radio range. Thus, from the perspective of a node forwarding a packet, the next hop depends on the width of the neighborhood it perceives. The analytical framework proposed in this paper allows to analyze the relationship between the energy efficiency of the routing tasks and the extension of the range of the topology knowledge for each node. A wider topology knowledge may improve the energy efficiency of the routing tasks but increases the cost of topology information due to signaling packets needed to acquire this information. The problem of determining the optimal topology knowledge range for each node to make energy efficient geographical routing decisions is tackled by integer linear programming. It is shown that the problem is intrinsically localized, i.e., a limited topology knowledge is sufficient to make energy efficient forwarding decisions. The leading forwarding rules for geographical routing are compared in this framework, and the energy efficiency of each of them is studied. Moreover, a new forwarding scheme, partial topology knowledge forwarding (PTKF), is introduced, and shown to outperform other existing schemes in typical application scenarios. A probe-based distributed protocol for knowledge range adjustment (PRADA) is finally introduced that allows each node to efficiently select online its topology knowledge range. PRADA is shown to rapidly converge to a near-optimal solution.

Wireless sensor networks (WSNs) are event-based systems that rely on the collective effort of several microsensor nodes. Reliable event detection at the sink is based on collective information provided by source nodes and not on any individual report. However, conventional end-to-end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. Hence, the WSN paradigm necessitates a collective event-to-sink reliability notion rather than the traditional end-to-end notion. To the best of our knowledge, reliable transport in WSN has not been studied from this perspective before. In order to address this need, a new reliable transport scheme for WSN, the event-to-sink reliable transport (ESRT) protocol, is presented in this paper. ESRT is a novel transport solution developed to achieve reliable event detection in WSN with minimum energy expenditure. It includes a congestion control component that serves the dual purpose of achieving reliability and conserving energy. Importantly, the algorithms of ESRT mainly run on the sink, with minimal functionality required at resource constrained sensor nodes. ESRT protocol operation is determined by the current network state based on the reliability achieved and congestion condition in the network. This self-configuring nature of ESRT makes it robust to random, dynamic topology in WSN. Furthermore, ESRT can also accommodate multiple concurrent event occurrences in a wireless sensor field. Analytical performance evaluation and simulation results show that ESRT converges to the desired reliability with minimum energy expenditure, starting from any initial network state.

Currently there is no control for real-time traffic sources in IP networks. This is a serious problem because real-time traffic can not only congest the network but can also cause unfairness and starvation of TCP traffic. However, it is not possible to apply current solutions for Internet to the networks with high bandwidth-delay products and high bit error rates. The channel errors may result in inaccurate congestion control decisions and unnecessary rate throttles leading to severe performance degradation. This problem is amplified in the links with high bandwidth-delay products, since the link is inefficiently utilized for a very long time until the unnecessary rate throttle is recovered. In this paper, a new Rate Control Scheme, RCS, is introduced for real-time interactive applications in networks with high bandwidth-delay products and high bit error rates. RCS is based on the concept of using dummy packets to probe the availability of network resources. Dummy packets are treated as low priority packets and consequently they do not affect the throughput of actual data traffic. Therefore, RCS requires all the routers in the connection path to support some priority policy. A new algorithm is also proposed to improve the robustness of the RCS to temporal signal loss conditions. The delay-bound considerations for real-time traffic sources using RCS rate control scheme are also investigated. Simulation experiments show that in environments with high bandwidth-delay products and high bit error rates, RCS achieves high throughput performance without penalizing TCP connections.

In the near future, small intelligent devices will be deployed in homes, plantations, oceans, rivers, streets, and highways to monitor the environment. These devices require time synchronization, so voice and video data from different sensor nodes can be fused and displayed in a meaningful way at the sink. Instead of time synchronization between just the sender and receiver or within a local group of sensor nodes, some applications require the sensor nodes to maintain a similar time within a certain tolerance throughout the lifetime of the network. The Time-Diffusion Synchronization Protocol (TDP) is proposed as a network-wide time synchronization protocol. It allows the sensor network to reach an equilibrium time and maintains a small time deviation tolerance from the equilibrium time. In addition, it is analytically shown that the TDP enables time in the network to converge. Also, simulations are performed to validate the effectiveness of TDP in synchronizing the time throughout the network and balancing the energy consumed by the sensor nodes.

Overlapping coverage areas of the systems in next generation networks cause high signaling overhead if the users are tracked in multiple systems independently. Selecting the system over which paging can be done is yet another problem. In this paper, we present a general next generation wireless network architecture and propose a location registration scheme that updates the location information only in the relevant subsystems. We also propose an efficient paging scheme that exploits the location information in multiple subsystems. User preferences, network availability, and connection history are considered while determining the subsystems to be used for location registration and paging.

In this paper, a new optimal policy is introduced to determine and adapt the generalized multiprotocol label switching (GMPLS) network topology based on the current traffic load. The integrated traffic engineering paradigm provides mechanisms for dynamic addition of physical capacity to optical networks. In the absence of such mechanisms, the rejection of incoming requests will be higher. The objective of the proposed policy is to minimize the costs involving bandwidth, switching and signaling. The policy is derived by utilizing the Markov decision process theory. The new policy is split into two levels: the MPLS network level and the optical network level. In addition to the optimal policy, a sub-optimal policy and a threshold-based policy are also proposed which are less computationally intensive but have comparable performance to the optimal policy. The proposed policies have been evaluated by simulation and compared to some heuristics. Numerical results, which show their effectiveness and the achieved performance improvement, are presented.

Since sensor networks can be composed of a very large number of nodes, the developed protocols for these networks must be scalable. Moreover, these protocols must be designed to prolong the battery lifetime of the nodes. Typical existing routing techniques for ad hoc networks are known not to scale well. On the other hand, the so-called geographical routing algorithms are known to be scalable but their energy efficiency has never been extensively and comparatively studied. For this reason, a novel analytical framework is introduced. In a geographical routing algorithm, the packets are forwarded by a node to its neighbor based on their respective positions. The proposed framework allows to analyze the relationship between the energy efficiency of the routing tasks and the extension of the range of the topology knowledge for each node. The leading forwarding rules for geographical routing are compared in this framework, and the energy efficiency of each of them is studied. Moreover partial topology knowledge forwarding, a new forwarding scheme, is introduced. A wider topology knowledge can improve the energy efficiency of the routing tasks but can increase the cost of topology information due to signaling packets that each node must transmit and receive to acquire this information, especially in networks with high mobility. The problem of determining the optimal knowledge range for each node to make energy efficient geographical routing decisions is tackled by integer linear programming. It is demonstrated that the problem is intrinsically localized, i.e., a limited knowledge of the topology is sufficient to take energy efficient forwarding decisions, and that the proposed forwarding scheme outperforms the others in typical application scenarios. For online solution of the problem, a probe-based distributed protocol which allows each node to efficiently select its topology knowledge, is introduced and shown to converge to a near-optimal solution very fast.

There exist several applications of sensor networks where reliability of data delivery can be critical. While the redundancy inherent in a sensor network might increase the degree of reliability, it by no means can provide any guaranteed reliability semantics. In this paper, we consider the problem of reliable sink-to-sensors data delivery. We first identify several fundamental challenges that need to be addressed, and are unique to a wireless sensor network environment. We then propose a scalable framework for reliable downstream data delivery that is specifically designed to both address and leverage the characteristics of a wireless sensor network, while achieving the reliability in an efficient manner. Through ns2 based simulations, we evaluate the proposed framework.

The next-generation wireless Internet (NGWI) is expected to provide a wide range of services including high-speed data and real-time multimedia to mobile users. To realize this expectation, a diverse set of challenges need to be addressed, which are posed by heterogeneous wireless networking environments within NGWI and the according application requirements. Furthermore, the architectural heterogeneities must be captured dynamically, while mobile users may roam during their connection duration. Current existing transport layer protocols have been developed for a specific network paradigm in mind, e.g., for wireless local area networks (WLANs), micro/macro wireless systems, or for satellite systems. Using these existing different transport layer protocols for NGWI to support global roaming of mobile users is not a practical solution due to processing and memory constraints of wireless terminals. Thus, there is a need for a unified adaptive transport layer protocol suite which can address the architectural heterogeneities for roaming mobile users and achieve the best performance for NGWI. In this paper, a unified adaptive transport layer (ATL) suite is introduced for NGWI which incorporates a new adaptive transport protocol (TCP-ATL) for reliable data transport and a new adaptive rate control protocol (RCP-ATL) for multimedia delivery in the NGWI. According to the requested service type, i.e., reliable data or multimedia, ATL selects the appropriate protocol. Both TCP-ATL and RCP-ATL, deploy a new adaptive congestion control method that dynamically adjusts the protocol configurations according to the current wireless network paradigms depending where the mobile user currently resides. Hence, the unified adaptive ATL protocol suite achieves high-throughput performance in all of underlying heterogeneous wireless architectures, i.e., WLANs, micro, macro, or satellite environments. Moreover, the developed adaptive congestion control explicitly takes fairness into consideration. Performance evaluation via simulation experiments reveals that the ATL protocol suite addresses the challenges posed by the NGWI and significantly improves the performance for reliable data and multimedia transport in NGWI.

Space exploration missions are crucial for acquisition of information about space and the Universe. The entire success of a mission is directly related to the satisfaction of its communications needs. For this goal, the challenges posed by the InterPlaNetary (IPN) Internet need to be addressed. Current transmission control protocols (TCPs) have very poor performance in the IPN Internet, which is characterized by extremely high propagation delays, link errors, asymmetrical bandwidth, and blackouts. The window-based congestion control, which injects a new packet into the network upon an ACK reception, is responsible for such performance degradation due to high propagation delay. Slow start algorithms of the existing TCPs further contribute to the performance degradation by wasting long time periods to reach the actual data rate. Moreover, wireless link errors amplify the problem by misleading the TCP source to unnecessarily throttle the congestion window. The recovery from erroneous window decrease takes a certain amount of time, which is proportional to the round-trip time (RTT) and further decreases the network performance. In this paper, a reliable transport protocol (TP-Planet) is presented for data traffic in the IPN Internet. It is intended to address the challenges and to achieve high throughput performance and reliable data transmission on deep-space links of the IPN Backbone Network. TP-Planet deploys a rate-based additive-increase multiplicative-decrease (AIMD) congestion control, whose AIMD parameters are tuned to help avoid throughput degradation. TP-Planet replaces the inefficient slow start algorithm with a novel Initial State algorithm, which allows the capture of link resources in a very fast and controlled manner. A new congestion detection and control mechanism is developed, which decouples congestion decisions from single packet losses in order to avoid the erroneous congestion decisions due to high link errors. In order to reduce the effects of blackout conditions on the throughput performance, TP-Planet incorporates the blackout state procedure into the protocol operation. The bandwidth asymmetry problem is addressed by the adoption of delayed selective acknowledgment (SACK). Simulation experiments show that the TP-Planet significantly improves the throughput performance and addresses the challenges posed by the IPN Backbone Network.

In this paper, a reliable multicast transport protocol TCP-Peachtree is proposed for satellite Internet protocol (IP) networks. In addition to the acknowledgment implosion and scalability problems in terrestrial wirelined networks, satellite multicasting has additional problems, i.e., different multicast topology, different type of congestion control problems, and low bandwidth feedback link. In TCP-Peachtree, the modified B+ tree logical hierarchical structure is used to form dynamic multicast groups. Local error recovery and acknowledgment (ACK) aggregations are performed within each subgroup and also via logical subgroups. In order to avoid the overall performance degradation caused by some worst receivers, a local relay scheme is designed. Two new algorithms, jump start and quick recovery, which are based on the usage of a type of low-priority segments called NIL segments, are proposed for congestion control. NIL segments are used to probe the availability of network resources and also for error recovery. The delayed selective acknowledgment (SACK) scheme is adopted to address the bandwidth asymmetry problems and a hold state is developed to address persistent fades. The simulation results show that the congestion control algorithms of TCP-Peachtree outperform the TCP-NewReno when combined with our hierarchical groups and improve the throughput performance during rain fades. It is also shown that TCP-Peachtree achieves fairness and is very highly scalability.

Bluetooth is an enabling technology for Personal Area Networks. A scatternet is an ad hoc network created by interconnecting several Bluetooth piconets, each with at most eight devices. Each piconet uses a different radio channel constituted by a frequency hopping code. The way the devices are grouped in different piconets and the way the piconets are interconnected greatly affect the performance of the scatternet in terms of capacity, data transfer delay, and energy consumption. There is a need to develop distributed scatternet formation algorithms, which guarantee full connectivity of the devices, reconfigure the network due to mobility and failure of devices, and interconnect them such a way to create an optimal topology to achieve gainful performance. The contribution of this paper is to provide an integrated approach for scatternet formation and quality-of-service support (called SHAPER-OPT). To this aim, two main procedures are proposed. First, a new scatternet formation algorithm called self-healing algorithm producing multihop Bluetooth scatternets (SHAPER) is developed which forms tree-shaped scatternets. A procedure that produces a meshed topology applying a distributed scatternet optimization algorithm (DSOA) on the network built by SHAPER is then defined. Performance evaluation of the proposed algorithms, and of the accordingly created scatternets, is carried out by using ns2 simulation. Devices are shown to be able to join or leave the scatternet at any time, without compromising the long term connectivity. Delay for network setup and reconfiguration in dynamic environments is shown to be within acceptable bounds. DSOA is also shown to be easy to implement and to improve the overall network performance.

Next-generation wireless Internet (NGWI) is expected to provide a wide range of services including real-time multimedia to mobile users. However, the real-time multimedia traffic transport requires rate control deployment to protect shared Internet from unfairness and further congestion collapse. The transmission rate control method must also achieve high throughput and satisfy multimedia requirements such as delay or jitter bound. However, the existing solutions are mostly for the wired Internet, and hence, they do not address the challenges in the wireless environments which are characterized by high bit error rates. In this paper, a new analytical rate control (ARC) protocol for real-time multimedia traffic over wireless networks is presented. It is intended to achieve high throughput and multimedia support for real-time traffic flows while preserving fairness to the TCP sources sharing the same wired link resources. Based on the end-to-end path model, the desired behavior of a TCP source over lossy links is captured via renewal theory. The resulting asymptotic throughput equation is designated as the driving equation for the proposed rate control method. Performance evaluation via simulation experiments reveals that ARC achieves high throughput and meets multimedia traffic expectations without violating good citizenship rules for the shared Internet.

User mobility profile (UMP) is a combination of historic records and predictive patterns of mobile terminals, which serve as fundamental information for mobility management and enhancement of quality of service (QoS) in wireless multimedia networks. In this paper, a UMP framework is developed for estimating service patterns and tracking mobile users, including descriptions of location, mobility, and service requirements. For each mobile user, the service requirement is estimated using a mean-square error method. Moreover, a new mobility model is designed to characterize not only stochastic behaviors, but historical records and predictive future locations of mobile users as well. Therefore, our approach incorporates aggregate history and current system parameters to acquire UMP. In particular, an adaptive algorithm is designed to predict the future positions of mobile terminals in terms of location probabilities based on moving directions and residence time in a cell. Simulation results are shown to indicate that the proposed schemes are effective on mobility and resource management by evaluating blocking/dropping probabilities and location tracking costs in wireless networks.

The preemption policy currently in use in MPLS-enabled commercial routers selects LSPs for preemption based only on their priority and holding time. This can lead to waste of resources and excessive number of rerouting decisions. In this paper, a new preemption policy is proposed and complemented with an adaptive scheme that aims to minimize rerouting. The new policy combines the three main preemption optimization criteria: number of LSPs to be preempted, priority of the LSPs, and preempted bandwidth. Weights can be configured to stress the desired criteria. The new policy is complemented by an adaptive scheme that selects lower priority LSPs that can afford to have their rate reduced. The selected LSPs will fairly reduce their rate in order to accommodate the new high-priority LSP setup request. Performance comparisons of a nonpreemptive approach, a policy currently in use by commercial routers, and our policies are also investigated.

Wireless sensor networks (WSN) are event based systems that rely on the collective effort of several microsensor nodes. Reliable event detection at the sink is based on collective information provided by source nodes and not on any individual report. Hence, conventional end-to-end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. However, the absence of reliable transport altogether can seriously impair event detection. Hence, the WSN paradigm necessitates a collective phevent-to-sink reliability notion rather than the traditional end-to-end notion. To the best of our knowledge, reliable transport in WSN has not been studied from this perspective before.In order to address this need, a new reliable transport scheme for WSN, the event-to-sink reliable transport (ESRT) protocol, is presented in this paper. ESRT is a novel transport solution developed to achieve reliable event detection in WSN with minimum energy expenditure. It includes a congestion control component that serves the dual purpose of achieving reliability and conserving energy. Importantly, the algorithms of ESRT mainly run on the sink, with minimal functionality required at resource constrained sensor nodes. ESRT protocol operation is determined by the current network state based on the reliability achieved and congestion condition in the network. If the event-to-sink reliability is lower than required, ESRT adjusts the reporting frequency of source nodes aggressively in order to reach the target reliability level as soon as possible. If the reliability is higher than required, then ESRT reduces the reporting frequency conservatively in order to conserve energy while still maintaining reliability. This self-configuring nature of ESRT makes it robust to random, dynamic topology in WSN. Analytical performance evaluation and simulation results show that ESRT converges to the desired reliability with minimum energy expenditure, starting from any initial network state.

IP mobility support is provided by the basic Mobile IP protocol. The main drawback of the protocol is that the packets must be routed along the paths longer than the optimal one. This is known as the triangle routing problem. Recently, the route optimization protocol was proposed to solve the triangle routing problem, which allows packets to be routed along an optimal path from a correspondent node to a mobile node. However, the route optimization protocol may cause high signaling and processing costs. In this paper, a new scheme for reducing costs in route optimization is introduced to solve the above problems. Link and signaling cost functions are introduced to capture the trade off between the network resources consumed by the routing, signaling, and processing load incurred by the route optimization. In this new scheme, route optimization is performed only when it minimizes the total cost function, which provides the optimal result from the point of view of link and signaling costs. The simulation results show that the proposed scheme provides the best performance.

A new scheme is developed for optimal location area design in wireless systems. New algorithms based on intercell traffic prediction and traffic-based cell grouping are used to select the optimal set of cells for location areas (LAs). The expected intercell movement patterns of mobiles are determined by using the new intercell traffic prediction algorithm. Further, the cells are partitioned into LAs by applying the new traffic-based cell grouping algorithm where the cell pairs with higher intercell mobile traffic are grouped into the same LA. Hence, the inter-LA mobile traffic is decreased by increasing the intra-LA mobile traffic. Experimental results show that this cell grouping algorithm reduces the number of location updates by 27 percent to 36 percent on average compared to proximity-based cell grouping schemes.

The explosive growth of the Internet has induced a need for developing tools to understand the composition and dynamics of the Internet traffic. Measurements of the various characteristics of a network provide insight into the state and performance of the network whether it is behaving as expected and whether changes in the network have improved or degraded its performance. Available bandwidth on the links of a network is an important metric which can predict the performance of the network. In this paper, an estimation algorithm for the available bandwidth on a link is presented. The algorithm estimates the available bandwidth and tells the duration for which the estimate is valid with a high degree of confidence. The algorithm dynamically changes the number of past samples that an used for prediction and also the duration for which the prediction holds.

As in terrestrial reliable multicasting, feedback implosion is a major problem in satellite multicast. The feedback implosion occurs when a large number of receivers sends their feedback to the satellite. A poker-game-based feedback suppression (PFS) algorithm is proposed for scalable satellite reliable multicast protocols. An analytical model is provided for the feedback suppression performance of the PFS scheme. This model is validated by simulation results. Numerical examples show that feedback can be effectively suppressed by introducing the PFS algorithm.

A multicast transport protocol, called TCP Peachtree, is proposed for satellite IP networks. In addition to the acknowledgment implosion and scalability problems appearing in terrestrial wirelined networks, satellite multicasting has additional problems, i.e., low bandwidth feedback link, different multicast topology and congestion control. In TCP Peachtree, the modified B+ tree hierarchical structure is used to form dynamic multicast groups. Local error recovery and ACK aggregations are performed within each subgroup and also via logical subgroups. Two new algorithms, jump start and quick recovery, which are based on a type of low priority segments, called NIL segments, are proposed for congestion control. NIL segments are used to probe the availability of network resources and also for error recovery. Moreover, an ACK filter is also introduced to aggregate ACKs. The simulation results show that the congestion control algorithms in TCP Peachtree outperform TCP NewReno when combined with our hierarchical groups and ACK filter. It is also shown that TCP Peachtree can have very good scalability.

This paper presents a new scheme to estimate the user mobility by incorporating the aggregate history of mobile users and system parameters. With this approach, each user's position within the location area is differentiated by zone partition for more accurate prediction. In order to provide the flexibility of tradeoff between quality demand and computation complexity, the estimation is adjusted dynamically according to the constraint of prediction order. Then an adaptive algorithm is developed to predict the future position of mobile terminals in terms of location probabilities, while considering each terminal's movement direction, residence time, and path information. Simulation results demonstrate that the signaling cost for location tracking under delay bound is greatly reduced based on the estimated user mobility pattern.

A new multicast routing algorithm is introduced for multi-layered satellite networks, which include GEO, MEO, and LEO layers. This scheme aims to minimize the total cost of multicast trees in the satellite network. Multicast trees are constructed and maintained in the dynamic satellite network topology in a distributed manner. Simulation results are provided to evaluate the performance of this scheme in terms of end-to-end delay and multicast tree cost.

Mobile IP is a solution for mobility on the global Internet. However, it does not extend well to highly mobile users. Mobile IP regional registration Is proposed to reduce the number of location updates to the home network, and reduce the signaling delay. This paper introduces an optimal regional location management mechanism for Mobile IP that results in the minimum signaling cost. A novel discrete analytical model is developed which captures the mobility and packet arrival pattern of a mobile terminal. This model does not impose any restrictions on the shape and the geographic location of Internet subnets. Given the average total location update and packet delivery cost, an iterative algorithm is then used to determine the optimal size of regional networks. Analytical results are also obtained to demonstrate how the optimal value changes under various parameters.

In this paper, a new preemption policy is proposed and complemented with an adaptive scheme that aims to minimize rerouting. The preemption policy combines the three main optimization criteria: number of LSP to be preempted, priority of LSP to be preempted, and amount of bandwidth to be preempted. The preemption policy is complemented by an adaptive scheme that selects LSP with lower priority and reduces their rate in order to accommodate the new high-priority LSP setup request. Heuristics for both preemption and adaptive preemption policies are derived. Simulation results show the heuristics' accuracy. Performance comparisons of a non-preemptive approach, our preemption policy, the adaptive rate policy, and the policy in use by commercial routers are included.

Mobile IP is a simple and scalable global mobility solution. However, it may cause excessive signaling traffic and long signaling delay. Mobile IP regional registration is proposed to reduce the number of location updates to the home network, and reduce the signaling delay. This paper introduces a novel distributed and dynamic regional location management for Mobile IP where the signaling burden is evenly distributed and the regional network boundary is dynamically adjusted according to the up-to-date mobility and traffic load for each terminal. In our distributed system, each user has its own optimized system configuration, which results in minimal signaling traffic. In order to find the signaling cost function, a new discrete analytical model is developed which captures the mobility and packet arrival pattern of a mobile terminal. This model does not impose any restrictions on the shape and the geographic location of subnets in the Internet. Given the average total location update and packet delivery cost, an iterative algorithm is then used to determine the optimal regional network size. Analytical results show that our distributed dynamic scheme outperforms the IETF Mobile IP regional registration scheme for various scenarios in terms of reducing the overall signaling cost. Using our approach, the system robustness is also enhanced.

Multiclass CDMA systems, which support multiple services with various quality of service (QoS) requirements, are studied. The focus is on the reverse link capacity and application of macrodiversity with maximal ratio combining (MMRC), where the signals from each mobile station (MS) are received by multiple base stations (BSs) and coherently combined. A simple analytical solution is first derived for the multiclass reverse link carrier-to-interference ratio (CIR). Using this CIR solution, a simple capacity analysis is developed in terms of the QoS requirements. Finally, the analysis is fully supported by simulation results.

The user mobility pattern (UMP) scheme is introduced for location update and paging in wireless systems where mobile terminals (MTs) maintain their history data in a database called user mobility history (UMH). During a location update, a UMP is derived from UMH and registered to the network. Unless the MT detects that it has moved out of the registered UMP, it does not perform any other location update. On the other hand, cells are paged selectively according to the cell entry times in the registered UMP upon a call arrival for the MT. The related data structures and the protocols for the UMP scheme are presented in the paper. The experimental results show that the UMP scheme outperforms the time-based and movement-based location update schemes as well as the blanket, selective, and velocity paging schemes.

Mobile IP is a simple and scalable global mobility solution. However, it may cause excessive signaling traffic and long signaling delay. Mobile IP regional registration is proposed to reduce the number of location updates to the home network and to reduce the signaling delay. This paper introduces a novel distributed and dynamic regional location management for Mobile IP where the signaling burden is evenly distributed and the regional network boundary is dynamically adjusted according to the up-to-date mobility and traffic load for each terminal. In our distributed system, each user has its own optimized system configuration which results in the minimal signaling traffic. In order to determine the signaling cost function, a new discrete analytical model is developed which captures the mobility and packet arrival pattern of a mobile terminal. This model does not impose any restrictions on the shape and the geographic location of subnets in the Internet. Given the average total location update and packet delivery cost, an iterative algorithm is then used to determine the optimal regional network size. Analytical results show that our distributed dynamic scheme outperforms the IETF Mobile IP regional registration scheme for various scenarios in terms of reducing the overall signaling cost.

Several IP-based routing algorithms have been developed for low-Earth orbit (LEO) satellite networks in recent years. The performance of the satellite IP networks can be improved drastically if multiple satellite constellations are used in the architecture. A multilayered satellite IP network is introduced that consists of LEO, medium-Earth orbit (MEO) and geostationary Earth orbit (GEO) satellites. A new multilayered satellite routing (MLSR) algorithm is developed that calculates routing tables efficiently using the collected delay measurements. The performance of the multilayered satellite network and MLSR is evaluated through simulations and analysis.

Satellite networks provide global coverage and support a wide range of services. Since low Earth orbit (LEO) satellites provide short round-trip delays, they are becoming increasingly important for real-time applications such as voice and video traffic. Many applications require a mechanism to deliver information to multiple recipients. A multicast routing algorithm for datagram traffic is introduced for LEO satellite IP networks. The new scheme creates multicast trees by using the datagram routing algorithm. The bandwidth utilization and delay characteristics are assessed through simulations.

Global wireless networks enable mobile users to communicate regardless of their locations. One of the most important issues is location management in a highly dynamic environment because mobile users may roam between different wireless systems, network operators, and geographical regions. A location-tracking mechanism is introduced that consists of intersystem location updates and intersystem paging. Intersystem update is implemented by using the concept of boundary location area, which is determined by a dynamic location update policy in which the velocity and the quality of service are taken into account on a per-user basis. Also, intersystem paging is based on the concept of a boundary location register, which is used to maintain the records of mobile users crossing the boundary of systems. This mechanism not only reduces location-tracking costs, but also significantly decreases call-loss rates and average-paging delays. The performance evaluation of the proposed schemes is provided to demonstrate their effectiveness in multitier personal communication systems.

To accomplish network layer integration of terrestrial and satellite IP networks, special exterior gateway protocols are needed. In this work, a new exterior gateway protocol called Border Gateway Protocol-Satellite version (BGP-S) is introduced that enables automated discovery of paths that go through the satellite network. This protocol is designed to work in only one terrestrial gateway in every autonomous system and enables the forwarding of discovered paths in the Internet using the BGP-4 protocol.

This paper presents an adaptive forward error correction (AFEC) protocol that provides a reliable communication service for real-time traffic over low-earth orbit (LEO) satellite networks. In time-varying wireless links, such as LEO satellite networks. A reliable channel estimation scheme with an appropriate code selection technique is essential for adaptive error-control systems. This paper proposes a new channel estimation scheme that uses receiver-initiated messages (ACKs, NAKs, and INCs). These messages feed back to the transmitter which then selects the code rate for sending packets. In addition, the scheme uses the concept of a dynamic transmittable code set by adjusting the maximum code rate in the set of possible codes from which the transmitter can select. In terms of throughput (from network provider's viewpoint) and packet error rate (from subscriber's viewpoint), performance results show that the proposed scheme guarantees the quality of service (QoS) requirements of real-time applications.

Currently there is no control for real-time traffic sources in IP networks. This is a serious problem because real-time traffic can not only congest the network but can also cause unfairness and starvation of TCP traffic. A new rate control scheme, RCS, is introduced for real-time traffic in networks with high bandwidth-delay products and high bit error rates. RCS is based on the concept of using dummy packets to probe the availability of network resources. Dummy packets are treated as low priority packets and consequently they do not affect the throughput of actual data traffic. Therefore, RCS requires all the routers in the connection path to support some priority policy. Simulation experiments show that in environments with high bandwidth-delay products and high bit error rates, RCS achieves good throughput performance without penalizing TCP connections.

An efficient signaling protocol for mobility application part (MAP) is essential to mobility support when mobile terminals roam between different networks in next generation wireless systems such as IMT-2000. In this paper, a new signaling protocol is proposed to reduce the overhead caused by mobility management, alleviating network load and consumption of network resources. Moreover, the new protocol effectively reduces the latency of call delivery and call loss rate due to crossing wireless systems with different standards and signaling protocols. Instead of performing location registration after a mobile user arrives at the new system, the mobile user is required to update its location information prior to its reaching the boundary of two systems. Results in this study demonstrate that the new protocol yields significant benefits in terms of reducing signaling costs, delays, and call loss rates.

Hierarchical code division multiple access (CDMA) cellular systems, consisting of macrocells with underlying microcells, are studied. We seek power control schemes which will allow both hierarchical layers to share the same spectrum. For the reverse link, hierarchical maximal ratio combining (HMRC) is applied where each mobile station (MSs) is received and coherently combined by base stations (BSs) in both layers. For the forward link, selective transmit diversity (STD) is applied where each BS provides multiple transmit paths for MSs to choose. We show that both HMRC and STD are effective in hierarchical CDMA architectures. We conclude that hierarchical architectures are a viable solution for improving CDMA cellular system capacity, and a significant performance gain can be achieved without assigning disjoint spectrum between the layers, by utilizing macrodiversity schemes such as HMRC and STD.

In next-generation wireless systems, one of the major features that is different from the current personal communication service systems is the seamless global roaming. The mobile subscribers will be allowed to move freely across different networks while maintaining their quality of service for a variety of applications. To meet this demand, the signaling protocol of mobility management must be designed, supporting location registration and call delivery for roaming users who move beyond their home network. A new signaling protocol is proposed, emphasizing the active location registration for ongoing services during the mobile subscribers' movement. Another important goal of this new protocol is to reduce the overhead caused by mobility management so that the signaling traffic load and consumption of network resources can be reduced. The new protocol efficiently reduces the latency of call delivery and call loss rate due to crossing wireless systems with different standards or signaling protocols. The numerical results reveal that the proposed protocol is effective in improving the overall system performance.

Current TCP protocols have lower throughput performance in satellite networks mainly due to the effects of long propagation delays and high link error rates. In this paper, a new congestion control scheme called TCP-Peach is introduced for satellite networks. TCP-Peach is composed of two new algorithms, namely Sudden Start and Rapid Recovery, as well as the two traditional TCP algorithms, Congestion Avoidance and Fast Retransmit. The new algorithms are based on the novel concept of using dummy segments to probe the availability of network resources without carrying any new information to the sender. Dummy segments are treated as low-priority segments and accordingly they do not effect the delivery of actual data traffic. Simulation experiments show that TCP-Peach outperforms other TCP schemes for satellite networks in terms of goodput. It also provides a fair share of network resources.

Satellite networks provide global coverage and support a wide range of services, low Earth orbit (LEO) satellites provide short round-trip delays and are becoming increasingly important. One of the challenges in LEO satellite networks is the development of specialized and efficient routing algorithms. In this work, a datagram routing algorithm for LEO satellite networks is introduced. The algorithm generates minimum propagation delay paths. The performance of the algorithm is evaluated through simulations. The robustness issues of the algorithm are also discussed.

When multimedia streams arrive at the receiver, their temporal relationships may be distorted due to jitter. Assuming the media stream is packetized, the jitter is then the packet's arrival time deviation from its expected arrival time. There are various ways to reduce jitter, which include synchronization at the application layer, or synchronization at the asynchronous transfer mode (ATM) adaptation layer (AAL). The new source rate recovery scheme called jitter time-stamp (JTS) provides synchronization at the ATM adaptation layer 2 (AAL2) which is used to carry variable bit-rate traffic such as compressed voice and video. JTS is implemented, and experiments have shown that it is able to recover the source rate.

A new adaptive forward-error-correction scheme (AFEC) is introduced at the link layer for TCP/IP data traffic in wireless ATM networks. The fading and interference in wireless links cause high and variable error rates, as well as bursty errors. The purpose of the AFEC scheme is to provide a dynamic error-control mechanism by using Reed-Solomon coding to protect the ATM cell payload, as well as the payload type indicator/cell loss priority fields in the ATM cell header. In order to enhance the error tolerance in cell framing and correct delivery, the AFEC scheme functions within a new concept called LANET framing and addressing protection mechanisms. The AFEC scheme has been validated using a simulation testbed of a low-speed wireless ATM network.

The geographical connection admission control (GCAC) algorithm is introduced for low Earth orbit (LEO) satellite networks. The GCAC scheme estimates the future handover blocking probability of a new call attempt based on the user location database, in order to decrease the handover blocking. By simulation, it is shown that the proposed GCAC scheme guarantees the handover blocking probability to a predefined target level. Since GCAC algorithm utilizes the user location information, performance evaluation shows that this technique also guarantees the target level of handover blocking probability in the nonuniform traffic pattern.

A novel paging scheme under delay bounds is proposed for personal communication systems. This paging scheme is independent of the location probability distributions of the mobile users and satisfies the delay bounds, while minimizing the amount of bandwidth used for locating a mobile user. The proposed paging scheme includes the optimal partition algorithm and paging procedure with respect to paging costs and average delays. The numerical results demonstrate that the proposed scheme is very effective in the minimization of the paging costs for location probability conditions such as uniform and non-uniform distributions.

Satellite networks provide global coverage and support a wide range of services. Low-Earth-orbit (LEO) satellites provide short round-trip delays and are becoming increasingly important. One of the challenges in LEO satellite networks is the development of specialized and efficient routing algorithms. In this work, a datagram routing algorithm for LEO satellite networks is introduced. The algorithm generates minimum propagation delay paths. The performance of the algorithm is evaluated through simulations and finally robustness issues are discussed.

Next-generation wireless communication is based on a global system of fixed and wireless mobile services that are transportable across different network backbones, network service providers, and network geographical boundaries. One of the most important problems for global wireless service is handoff management. In this paper, a new handoff technique is introduced which supports mobility between dissimilar networks. First, the system architecture is described, based on the concept of a boundary cell region between networks. Then a new inter-system handoff protocol is presented that uses boundary cells that allow the mobile terminal to roam into a different network. The performance of the protocol is analyzed in terms of the additional inter-system handoff signaling time and the minimum boundary cell area threshold for a successful transition within the prescribed time constraints.

Global wireless networks enable mobile users to communicate regardless of their locations. One of the most important issues is location management in a highly dynamic environment because mobile users may roam between different wireless networks, network operators, and geographical regions. In this paper, a location tracking mechanism is introduced, which consists of intersystem location updates using the concept of boundary location area (BLA) and paging using the concept of boundary location register (BLR). The BLA is determined by a dynamic location update policy in which the velocity and the quality of service (QoS) are taken into account on a per-user basis. The BLR is used to maintain the records of mobile users crossing the boundary of networks. This mechanism not only reduces location tracking costs but also significantly decreases call loss rates and average paging delays. The performance evaluation of the proposed schemes is provided to demonstrate their effectiveness in multitier wireless networks.

New paging schemes are presented for locating mobile users in wireless networks. Paging costs and delay bounds are considered since the paging cost is associated with bandwidth utilization and delay bounds influence call setup time. In general, location tracking schemes require intensive computation to search for a mobile terminal in current PCS networks. To reduce the paging cost, three new paging schemes-reverse, semi-reverse and uniform-are introduced to provide a simple way of partitioning the service areas and accordingly minimizing the paging cost based on each mobile terminal's location probability distribution. Numerical results demonstrate that our approaches significantly reduce the paging cost for various location probability distributions such as uniform, truncated discrete Gaussian, and irregular distributions.

This paper proposes a new approach to simplify the two-dimensional random walk models capturing the movement of mobile users in personal communications services (PCS) networks. Analytical models are proposed for the new random walks. For a PCS network with hexagonal configuration, our approach reduces the states of the two-dimensional random walk from (3n/sup 2/+3n-5) to n(n+1)/2, where n is the layers of a cluster. For a mesh configuration, our approach reduces the states from (2n2-2n+1) to (n/sup 2/+2n+4)/4 if n is even and to (n/sup 2/+2n+5)/4 if n is odd. Simulation experiments are conducted to validate the analytical models. The results indicate that the errors between the analytical and simulation models are within 1%. Three applications (i.e., microcell/macrocell configuration, distance-based location update, and GPRS mobility management for data routing) are used to show how our new model can be used to investigate the performance of PCS networks.

This paper describes current and proposed protocols for mobility management for public land mobile network (PLMN)-based networks, mobile Internet protocol (IP) wireless asynchronous transfer mode (ATM) and satellite networks. The integration of these networks will be discussed in the context of the next evolutionary step of wireless communication networks. First, a review is provided of location management algorithms for personal communication systems (PCS) implemented over a PLMN network. The latest protocol changes for location registration and handoff are investigated for mobile IP followed by a discussion of proposed protocols for wireless ATM and satellite networks. Finally, an outline of open problems to be addressed by the next generation of wireless network service is discussed.

In future wireless multimedia networks, there will be a mixture of different traffic classes which have their own maximum tolerable bit error rate (BER) requirements. In this paper, a novel medium access control (MAC) protocol called wireless multimedia access control protocol with BER scheduling (in short form, WISPER) for CDMA-based systems is proposed. WISPER utilizes the novel idea of scheduling the transmission of multimedia packets according to their BER requirements. The scheduler assigns priorities to the packets, and performs an iterative procedure to determine a good accommodation of the highest-priority packets in the slots of a frame so that packets with equal or similar BER requirements are transmitted in the same slots. The proposed WISPER protocol has been validated using a software emulator on the cellular environment. Performance evaluation results based on the implementation are also included.

This paper describes the design and performance of a new ARQ protocol for wireless ATM networks. The wireless channel is characterized by a higher and variable error rate in comparison with fiber-based networks for which ATM was designed. The purpose of the protocol is to provide a capability to dynamically support ATM-based communications in a fluctuating transmission environment by using selective retransmission. The key ideas in the protocol design consist of variable packet size and periodic status message. The packet size is changed adaptively with the optimal size according to the time-varying conditions of the wireless channel, as a result maximizing the throughput efficiency. The proposed protocol has been validated using a software emulator which incorporates a wireless channel model. Experimental performance results based on the implementation are presented.

The routing techniques used in conventional packet radio networks are not suitable for dynamic multihop wireless networks because of their unique architecture. In this paper a new hierarchical multihop routing algorithm is introduced which balances the cost of location-update and path-finding operations by partitioning the terminals and mobile base stations to produce a virtual topology. Based on the virtual topology each network entity stores a fraction of the network topology information and maintains the routing efficiency. Finally, the performance of the hierarchical multihop routing algorithm is investigated through simulations.

Low Earth Orbit (LEO) satellite networks require a reliable handover re-routing protocol that is critical for connections with multihop intersatellite links (ISLs). In this paper, we introduce a footprint handover re-route protocol (FHRP) that maintains the optimality of the initial route without performing a routing algorithm after satellite handovers. Furthermore, the FHRP handles the inter-orbit handover problem. The FHRP makes use of the footprints of the satellites in the initial route as the reference for re-routing. More specifically, after an optimum route has been determined during the call establishment process, the FHRP ensures that the new route due to handover is also optimum. The FHRP is applicable to any type of connectionoriented networks. The adaptation of the FHRP to the widely accepted ATM technology, which will be employed in future satellite networks, is also addressed in this paper. The FHRP demands easy processing, signaling, and storage costs. The performance re...

This paper introduces a dynamic hierarchical database architecture for location management in personal communications service (PCS) networks. The proposed scheme allows the dynamic adjustments of user location information distribution based on the mobility and calling patterns of the mobile terminals (MTs). A unique distribution strategy is determined for each MT, and location pointers are set up at selected remote locations which indicate the current location of the MTs. This method effectively reduces the signaling and database access overhead for location registration and call delivery. Besides, the required processing is handled by a distributed network of directory registers and centralized coordination is not necessary. The functions of the other network elements, such as the home location register (HLR) and the visitor location registers (VLRs), remain primarily unchanged. This greatly facilitates the deployment of this scheme in current PCS networks.

The shadow cluster concept can be used to estimate future resource requirements and to perform call admission decisions in wireless networks. Shadow clusters can be used to decide if a new call can be admitted to a wireless network based on its quality-of-service (QoS) requirements and local traffic conditions. The shadow cluster concept can especially be useful in future wireless networks with microcellular architectures where service will be provided to users with diverse QoS requirements. The framework of a shadow cluster system is completely distributed, and can be viewed as a message system where mobile terminals inform the base stations in their neighborhood about their requirements, position, and movement parameters. With this information, base stations predict future demands, reserve resources accordingly, and admit only those mobile terminals which can be supported adequately. The shadow cluster concept involves some processing and communication overheads. These overheads have no effect on wireless resources, but only on the base stations and the underlying wireline network. It is shown how base stations determine the probabilities that a mobile terminal will be active in other cells at future times, define and maintain shadow clusters by using probabilistic information on the future position of their mobile terminals with active calls, and predict resource demands based on shadow cluster information. In addition, a call admission algorithm is introduced, which uses current traffic and bandwidth utilization conditions, as well as the amount of resources and maximum allowable "dropping probability" being requested. Performance results showing the advantages of the shadow cluster concept are also included.

The Available-Bit-Rate (ABR) service that is being standardized by the ATM Forum dynamically determines the maximum transmission rate, so-called explicit rate, of a connection. A drawback of the ABR control scheme for calculating the explicit rates is that it tries to allocate the same bandwidth to all ABR connections regardless of the application type of the connection. In this study a multi-level explicit rate scheme is proposed that can allocate different explicit rates for different classes of connections. ABR traffic is controlled at three levels. At the topmost level, bandwidth is dynamically regulated between CBR, VER, and ABR traffic sources. At the next level, bandwidth is controlled between different classes of ABR traffic. At the lowest level bandwidth is distributed among connections belonging to the same ABR traffic class. The effectiveness of the proposed scheme is demonstrated in simulation experiments.

This paper presents an analysis of the anchor radio system (RS) handover method for the Personal Access Communications System (PACS). This handover method provides a simple yet effective solution without adding new requirements to the existing network infrastructures. Based on this technique, inter-RS and inter-switch handovers can be achieved using a new RS-to-RS interface called inter-RS interface (IRI). This paper first describes the use of the IRI protocol among PACS based RSs. Then it proposes an analytical model for the Anchor RS handover method to determine the expected handover delay under given mobility, call duration and signaling delay parameters.

Unlike traditional data traffic, real time multimedia traffic requires synchronization. Temporal relationships among media must be maintained. Yet delay jitter and the absence of a global clock may disrupt these temporal relationships. This paper introduces new group synchronization protocols for real-time, multimedia applications, including teleconference, teleorchestration and multimedia on demand services. The proposed protocols achieve synchronization for all configurations (one-to-one, one-to-many, many-to-one, and many-to-many), and does so without prior knowledge of the end-to-end delay distribution, or the distribution of the clock drift. The only a-priori knowledge the protocols require is an upper bound on the end-to-end delay. The paper concludes with simulation experiments showing that the protocols work effectively in both LAN and WAN environments.

Augmented Binary Hypercube (AH) architecture consists of the binary hypercube processor nodes (PNs) and a hierarchy of management nodes (MNs). Several distributed algorithms maintain subcube information at the MNs to realize fault tolerant, fragmentation free processor allocation and load balancing. For efficient implementation of AH, we map MNs onto PNs, define and prove infeasibility of ideal mappings. We propose easily implementable nonoptimal mappings, having negligible overheads on performance. Extensive simulation studies and performance analysis conclude that these algorithms realize significantly better average job completion time and higher processor utilization, as compared to the best sequential allocation schemes and parallel implementation of Free List. AH algorithms can be tuned or adapt to the job and system characteristics, and resource management traffic.

This paper introduces a mobility tracking mechanism that combines a movement-based location update policy with a selective paging scheme. Movement-based location update is selected for its simplicity. It does not require each mobile terminal to store information about the arrangement and the distance relationship of all cells. In fact, each mobile terminal only keeps a counter of the number of cells visited. A location update is performed when this counter exceeds a predefined threshold value. This scheme allows the dynamic selection of the movement threshold on a per-user basis. This is desirable as different users may have very different mobility patterns. Selective paging reduces the cost for locating a mobile terminal in the expense of an increase in the paging delay. We propose a selective paging scheme which significantly decreases the location tracking cost under a small increase in the allowable paging delay. We introduce an analytical model for the proposed location tracking mechanism which captures the mobility and the incoming call arrival patterns of each mobile terminal. Analytical results are provided to demonstrate the cost-effectiveness of the proposed scheme under various parameters.

A personal communications network (PCN) location tracking scheme called local anchoring is introduced which reduces the signalling cost as compared to the location management strategy proposed in the IS-41 standard. Local anchoring reduces the number of location registration messages between the home location register (HLR) and the visitor location registers (VLRs) in a way that location change is reported to a nearby VLR called the local anchor (LA) instead of to the HLR. This method successfully reduces the cost for location tracking when the call arrival rate is low relative to the mobility rate and the cost for location registration is high. A dynamic local anchoring mechanism is then introduced which dynamically selects the LA such that the expected cost for location registration and call delivery can be further reduced. It is demonstrated that the cost of dynamic local anchoring is always lower than or equal to that of the IS-41 scheme.

A novel bandwidth regulation mechanism is proposed which improves the ability of a packet-switching network to cope with multiple real-time and non-real-time traffic classes. The mechanism achieves regulation of link bandwidth at two levels. At the first level, bandwidth is dynamically regulated between different traffic classes. The concept of 'inter-class regulation' is introduced which enforces that the bandwidth left unused by a traffic class is divided among traffic classes with high bandwidth demands. At the second level, bandwidth regulation is enforced on end-to-end traffic streams, so-called flows, such that flows from the same class with identical routes have the same throughput constraints. This concept is referred to as 'intra-class regulation'. A simple distributed protocol is presented that achieves a intra-class and inter-class regulation in a general internetwork. The effectiveness of the protocol is demonstrated by simulation experiments.

A Personal Communication Network (PCN) location tracking scheme called “local anchoring” is introduced which reduces the signaling cost as compared to the location strategy proposed in the IS-41 standard. Local anchoring minimizes the number of location registration messages between the home location register (HLR) and the visitor location registeras (VLRs) in a way that location change is reported to a nearby VLR called the local anchor (LA) instead of to the HLR. This method successfully reduces the cost for location tracking when the call arrival rate is low relative to the mobility rate and the cost for location registration is high. A dynamic local anchoring mechanism is then introduced which dynamically selects the LA such that the expected cost for location registration and call delivery is minilnized. Experimental results demonstrated that the cost of dynamic local anchoring is always lower than OF equal to that of the IS-41 scheme.

This paper describes the Shadow Cluster concept, a novel idea that can be used to improve the resource allocation and the call admission procedures in wire less networks.Shadow clusters can be used to allocate resources that need to be reserved for call hand-offs, and to determine if a new call should be admitted to a wireless network based on the call's requirements and local traffic conditions.The shadow cluster concept is targeted for ATM-based wireless networks with a micro/n.ano-cellulararchitecture, where service will be provided to users with very diverse requirements.In these n.etworks, and as a consequence of the small cell sizes, mobile users will typically experience a high number of cell hand-offs during their connections' lifetime.'With shadow clust.ers, the quality of service of mobile calls can be improved by reducing the number of dropped calls during hand-offs, and by disallowing the establishment of new calls that are highly likely to later result in a dropped call.The framework of a shadow cluster system is completely distributed, and can be viewed as a message system where a mobile terminal informs the base stations in the neighborhood about i.ts requirements, position, and movement parameters, so that the base stations project future demands, reserve resources accordingly, and admit onlv

A mobile user location management mechanism is introduced that incorporates a distance based location update scheme and a paging mechanism that satisfies predefined delay requirements. An analytical model is developed which captures the mobility and call arrival pattern of a terminal. Given the respective costs for location update and terminal paging, the average total location update and terminal paging cost is determined. An iterative algorithm is then used to determine the optimal location update threshold distance that results in the minimum cost. Analytical results are also obtained to demonstrate the relative cost incurred by the proposed mechanism under various delay requirements.

A new multiple access protocol called PROTON (PROTocol for Optical Networks) is developed for optical local area networks based on a passive star topology. PROTON uses wavelength division multiplexing (WDM) and is highly bandwidth-efficient. One of the available wavelengths is used as a control channel. Time is divided into fixed-sized slots. The size of the slots is the same for the control and the data channels. Before transmitting a packet, a station must compete with others for a slot in a data wavelength, using a collision-free procedure. Transmitting stations and the corresponding wavelengths for their data transmissions are determined at each station by a simple arbitration scheme. The protocol is suitable for networks where the number of users can be much larger than the number of available data channels. In addition to propagation delays, it is considered that transmitter and receiver tuning times as well as the times required to process control packets are not negligible. Whenever possible, and to maximize the throughput of the network, tuning and processing times of transmitters and receivers are overlapped with each other and with data transmission times. Also, data slot requests and packet transmissions are scheduled in a pipeline fashion, thus reducing the detrimental effects on throughput and packet delay of long propagation delays. The paper includes an analysis of the maximum throughput characteristics of PROTON. An analytical model is developed, and several performance measures are obtained.>

It has previously been found that feedback in an ATM network is useful in the long run to alleviate congestion. This general conclusion, although theoretically important, does not address the practical concern as to how the network behaves when it is adjusting itself in the short to medium range. The work reported in the paper is motivated by this practical concern. A new feedback based dynamic traffic control mechanism (called the balanced mechanism) is proposed and compared with the pure preventive congestion control (PCC) and an existing feedback based mechanism, known as explicit forward congestion notification (EFCN). It is shown that the balanced mechanism outperforms both PCC and the EFCN.>

A serious fairness problem occurs whenever homogeneous, variable bit-rate, video traffic streams are multiplexed at a finite buffer statistical multiplexer. Namely, the cell loss ratio performance varies widely across individual traffic streams. The cause of the problem is the particular random relation of the periodic frame transmission epochs of the video sources that feed the multiplexer. In this paper a protocol is presented which controls the frame transmission epochs, in order to achieve fair distribution of losses among the admitted connections. The protocol operates with the participation of the sources by imposing an additional per-source delay on the traffic entering the network. These additional delays are calculated whenever a connection is accepted or terminated. The overall additional delay imposed by the protocol is guaranteed to be minimal through the use of an appropriate optimization algorithm. The performance of the proposed protocol, operating in conjunction with the optimization algorithm, is simulated and evaluated. A basic framework is given for its implementation on an ATM network. Finally, the issues of buffer overhead and the impact of the protocol on the delay experienced at the multiplexer are also discussed.

A protocol with strictly preemptive priorities that does not admit low-priority traffic if the load from high-priority traffic exceeds the capacity of the transmission channel in a MAN is presented. The protocol guarantees fairness for transmissions at the highest priority level. By introducing a general characterization of bandwidth allocation schemes for dual bus networks, existing priority mechanisms can be categorized according to the provided quality of service. The unique existence of a bandwidth allocation scheme for multiple priority traffic is shown with a full utilization of the channel capacity, with a fair distribution of bandwidth respective to traffic from a particular priority level, and with preemptive priorities. The performance of the presented protocol is compared to existing proposals for multiple priority mechanisms. It is shown that adopting the new protocol results in shorter access delays for high-priority transmissions. The protocol allows the stations of the network to react quickly to load changes. It is shown that the effectiveness of the priority scheme, compared to priority schemes using the bandwidth-balancing mechanism, is less dependent on increasing the transmission speed of the network.>

A media access protocol that achieves a fair distribution of the bandwidth in one round-trip delay is presented. The protocol is based on a unique solution to a fair and waste-free bandwidth allocation. This bandwidth allocation can be implemented in a distributed manner. A comparison of the new protocol with the DQDB (distributed queue dual bus) protocol shows considerable advantages regarding the transmission delay of messages and the time a station needs to obtain a fair portion of the available bandwidth. The advantages of the protocol become more apparent for large networks and high transmission speeds. In addition, the new protocol can perform nonuniform bandwidth allocations.>

An indexing scheme called partitioned global indexes (PGI) for a locally distributed database system is presented. The scheme builds a global index for the entire relation and partitions the index across the sites. A strategy for processing such an index is also presented. In order to evaluate the performance of the scheme, a simulation model is developed. The simulation results are compared to the classical scheme, called partial indexes (PI), in which corresponding index and data entries are stored at the same site. The advantages and disadvantages of the indexing schemes when processing conjuctive queries are analytically investigated. Analysis and simulation experiments show that tradeoffs between the new and the classical scheme.>

A protocol for dual bus networks that does not show the disadvantages inherent in the IEEE 802.6 standard for metropolitan area networks is proposed. The protocol obtains a fair distribution of bandwidth after a time equal to one round-trip delay and allows a full utilization of the available bandwidth. The protocol is derived from a fair and waste-free bandwidth allocation scheme. The features of the protocol can be included in the existing IEEE 802.6 standard. It is shown that the proposed protocol has significant performance advantages over the IEEE 802.6 standard.>

The authors analyze an M/sub 1/, M/sub 2//G/sub 1/, G/sub 2//1/N queue with different scheduling and push-out schemes. They present an exact method to compute loss probabilities, the distribution of the number of class 1 packets in the system and the mean waiting time of a class 1 packet. An approximate solution is given for the computation of the mean waiting time for class 2 packets. The model allows general service time distributions for classes 1 and 2, as well as a general service discipline and a divided buffer management scheme. Numerical examples are included, which consider the loss probabilities and mean waiting time simultaneously.>

A dynamic window model is developed which provides admission control for circuit switched networks through the signaling network. This model incorporates distributed processing while achieving desired global congestion control effects. It reflects the interaction between the circuit switched path in the telephone network and the packet switched path in the signaling network. The model is solved by applying the concept of parametric analysis to study the whole circuit switching subnetwork as a composite server. The variant service rate is derived for the composite server of the circuit switch trunk in the context of a closed chain where the arrival of call services is finite. To avoid overflow and combinatorial complex problems, the computation is reduced to the Erlang recursive form. Mean value analysis formulas are derived for the model. Examples are given to demonstrate the validation of the analysis.>

Two questions are examined, regarding real-time multiprocessor scheduling for large-scale nonuniform memory access (NUMA) architectures: how are the latency and the quality of scheduling affected by different degrees of completeness in the information shared among multiple potentially concurrent schedules, and how can scheduling information be represented so that it is efficiently and concurrently accessible? The authors present a real-time scheduling algorithm for multiprocessors that is scalable in the number of tasks performing scheduling and in the maximum amount of computation time consumed by those tasks. They also develop a flexible representation for shared information within the distributed scheduler that is easily varied regarding its degree of information completeness. It is then shown that the sharing of incomplete (vs. complete) information can lead to increased performance regarding scheduling latency with few or no losses in scheduling quality. In addition, it is shown that this holds for a variety of parallel machines, ranging from NUMA to distributed memory machines.>

The IEEE 802.6 standard for Metropolitan Area Networks does not provide multiple priority traffic for connectionless data services. A priority mechanism that was considered for the standard showed to be not effective. As of now, there exists no protocol for multiple access dual bus networks that is able to implement pre-emptive priorites and, at the same time, can satisfy minimal fairness requirements for transmissions at the highest priority level. In this study, a protocol with strictly pre-emptive priorities, i.e., a protocol that does not admit low priority traffic if the load from high priority traffic exceeds the capacity of the transmission channel, is presented. The protocol is derived from a unique bandwidth allocation scheme with a full utilization of the bus capacity, with a fair distribution of bandwidth respective to traffic from a particular priority level and with pre-emptive priorities. The performance of the presented protocol is compared to a priority mechanism that is based on the bandwidth balancing mechanism. It is shown that adopting the new protocol results in shorter access delays for high priority transmissions.

The behavior of n interacting processes synchronized by the “Time Warp” rollback mechanism is analyzed under the constraint that the total amount of memory to execute the program is limited. In Time Warp, a protocol called “cancelback” has been proposed to reclaim storage when the system runs out of memory. A discrete state, continuous time Markov chain model for Time Warp augmented with the cancelback protocol is developed for a shared memory system with n homogeneous processors and homogeneous workload. The model allows one to predict speedup as the amount of available memory is varied. To our knowledge, this is the first model to achieve this result. The performance predicted by the model is validated through direct performance measurements on an operational Time Warp system executing on a shared-memory multiprocessor using a workload similar to that in the model. It is observed that Time Warp with only a few additional message buffers per processor over that required in the corresponding sequential execution can achieve approximately the same or even greater performance than Time Warp with unlimited memory, if GVT computation and fossil collection can be efficiently implemented.

This work analyses a multiprocessor system in which processes communicate with each other via buffers using SEND and WAIT operations. Since the buffers are of finite capacity, a process which cannot execute a synchronisation operation successfully must leave the processor and go into the blocking state. The analysis of the multiprocessor system is executed hierarchically using two models – (Global Model and Process Communication Model). The interprocess communication is analysed by using the process communication model, a closed queueing network model with finite station capacities. An analytical method is developed for the solution of the process communication model. The method provides exact results for two-station cases and accurate approximate results for multiple station cases. The blocking probabilities and the blocking times of processes are computed from the process communication model and are used as input parameters for the global model which can then be solved by appropriate existing product form network methods. The performance measures such as utilisation, throughput, mean response time, mean queue length, and in particular, the blocking overhead due to the process communication, are obtained. The analytical results are validated by simulation of the entire system.

Integrated schemes of routing, flow control, and congestion control in packet-switched networks are investigated for performance optimization. After the control parameters and objective function are introduced, an efficient method is derived to compute the gradient vector and Hessian matrix of such an objective function. The method, used with a general nonlinear programming strategy, solves this nonlinear optimization problem. Several examples which showed efficient and stable behavior were investigated. The results obtained by the proposed method are compared with exact values and are shown to be accurate.>

The general behaviour of the automatic repeat request (ARQ) protocols is modeled by a queueing network with priorities representing the erroneous and recovery processes. A mean value analysis algorithm is developed for the performance analysis of the model. The input parameters, the erroneous period and the recovery duration, for the model are gained from the extended finite state machine model description of the protocols. By giving several examples the authors demonstrate the general applicability of the new approach.>

The behavior of n interacting processors synchronized by the "Time Warp" protocol is analyzed using a discrete state continuous time Markov chain model. The performance and dynamics of the processes are analyzed under the following assumptions: exponential task times and times-tamp increments on messages, each event message generates one new message that is sent to a randomly selected process, negligible rollback, state saving, and communication delay, unbounded message buffers, and homogeneous processors that are never idle. We determine the fraction of processed events that commit, speedup, rollback probability, expected length of rollback, the probability mass function for the number of uncommitted processed events, and the probability distribution function for the virtual time of a process. The analysis is approximate, so the results have been validated through performance measurements of a Time Warp testbed (PHOLD workload model) executing on a shared memory multiprocessor.

A solution algorithm is developed for higher moments of the number of jobs at the stations in load-dependent mixed product form queuing networks. Such networks are important because they can be used to model computer systems and computer communication networks. A relationship is proved and applied between the derivatives of these moments and higher moments. The derivative measures are calculated using a mean value analysis type algorithm called moment analysis. The authors describe the model and review the product form solutions for load-dependent mixed queuing networks. They develop the moment analysis algorithm and the formulas for the performance measures such as the response time, throughput and mean number of jobs in the stations. The complexity of the algorithm is discussed.>

The behavior of n interacting processors synchronized by the Time Warp protocol is analyzed using a discrete-state, continuous-time Markov chain model. The performance and dynamics of the processes (or processors) are analyzed under the following assumptions: exponential task times and timestamp increments on messages, each event message generates one new message that is sent to a randomly selected process, negligible rollback, state saving, and communication delay, unbounded message buffers, and homogeneous processors. Several performance measures are determined, such as: the fraction of processed events that commit, speedup, rollback probability, expected length of rollback, the probability mass function for the number of uncommitted processed events, the probability distribution function for the virtual time of a process, and the fraction of time the processors remain idle. The analysis is approximate, thus the results have been validated through performance measurements of a Time Warp testbed executing on a shared-memory multiprocessor.>

The following configurations of interconnected networks are studied: (i) the gateways and the channels of local area networks have no buffer capacity constraints; (ii) only gateways have buffer capacity constraints; (iii) only the channels of local area networks have buffer capacity constraints; and (iv) both the gateways and the channels of the local area networks have buffer capacity constraints. An approximation method that makes it possible to compute the throughput for the above network configurations is introduced. Examples are given to demonstrate the effects of gateway buffer capacity on the performance of the network. Approximate results are validated by simulation.>

One way to show that a system is not secure is to demonstrate that a malicious or mistake-prone user or program can break security by causing the system to reach a nonsecure state. A fundamental aspect of a security model is a proof that validates that every state reachable from a secure initial state is secure. A sequential security model assumes that every command that acts as a state transition executes sequentially, while a concurrent security model assumes that multiple commands execute concurrently. This paper presents a security model called the Centralized-Parallel-Distributed model (CPD model) that defines security for logically, or physically centralized, parallel, and distributed systems. The purpose of the CPD model is to define concurrency conditions that guarentee that a concurrent system cannot reach a state in which privileges are configured in a nonsecure manner. As an example, the conditions are used to construct a representation of a distributed system.

A method is developed which allows the application of Norton's theorem on queuing networks with finite capacities. A node is arbitrarily selected and the subnetwork containing all remaining nodes is replaced by a composite node with infinite capacity; thus the entire network is reduced to a two-node network having the node of interest and the composite node. Although blocking causes interdependencies between nodes in the network, the selected node is totally isolated from the rest of the network by constructing phases in the server which reflect the blocking events. An algorithm is given to compute the parameters of the phases. Several examples are discussed to demonstrate the efficiency and generality of the technique. Comparisons with simulation results show that the proposed technique provides accurate results for throughput values.>

A description is given of the hierarchical model (HM), an access matrix-based model used to define nondisclosure in distributed multilevel secure applications such as secure file systems, secure switches, and secure upgrade downgrade facilities. The HM explicitly encodes access rights, synchronization primitives, and indirection in its state matrix. Serializability of concurrent commands is formally defined in terms of the HM syntactic model of computation. HM serializability conditions are independent of the semantic security predicate. Finally, an example that illustrates the HM is presented.>

It is shown that the equilibrium-state probabilities for this type of blocking queuing network have an approximate product-form solution, which is based on normalizing the infeasible states that violate station capacities. To obtain the throughput values, a state-space transformation is introduced. This concept is based on finding a nonblocking network with an appropriate total number of jobs of which the number of feasible states is equal or approximately equal to the number of feasible states in the blocking queuing network. This guarantees that the Markov processes describing the evolution networks over time have approximately the same structure, so the throughputs of both systems are approximately equal. The approximations are validated by executing several examples and comparing them with simulation results.>

A message-switched network with local and global window flow controls is analyzed. Messages arriving to find the global window full or the first destination's local window full are assumed to be lost. Further, if a message from a source system is sent to a destination system of which the local window is full, the message blocks the source system until it can be received from the destination. In that time, no other message can be processed by the source system. An open tandem queueing network model with blocking is developed where the service times are assumed to be general and the scheduling disciplines are first-come, first-served. An approximation algorithm for the effective computation of performance measures, such as the throughput of the system, mean number of messages in the global window, and the mean delay time of the system, is given. The approximation has been validated by several examples; comparing the analytical results with simulation demonstrates good agreement.>

An approximation is introduced for the mean value analysis of queueing networks with transfer blocking. The blocking occurs when a job, after completing service at a station, wants to join a station which is full. The job resides in the server of the source station until a place becomes available in the destination station. The approximation is based on the modification of mean residence times, due to the blocking events that occur in the network. Several examples are executed that validate the approximate results.>

A method for obtaining approximate solutions to load-dependent closed queueing networks containing general service-time distributions and first-come-first-served scheduling disciplines is presented. The technique demonstrated is an extension of the well-known method of R. Marie (1979). A formula for the conditional throughputs is derived. After each iteration a check is performed to guarantee that the results obtained are within a tolerance level epsilon . These iterations are repeated whenever invalid results are detected. On the average, the solutions obtained vary by less than 5% from their respective exact and simulation results.>