The rapid evolution of Beyond 5G (B5G) and 6G networks introduces unprecedented complexity in network management due to their support for advanced services like realtime extended reality (XR) and large-scale IoT applications. Traditional AI models, which primarily rely on predictive and correlation-based approaches, struggle to capture the intricate interactions within these multi-layered systems. This paper explores Hierarchical Causal Models (HCMs) as an effective solution to model nested, cross-layer, and infrastructure-level causal relationships. We demonstrate how HCMs provide deeper insights into network behavior and performance optimization compared to flat models. Practical considerations for implementing HCMs are discussed, with attention to challenges such as model complexity and data requirements. In all, HCMs hold significant potential for improving network management in$\mathbf{6 G}$environments.

With the growing number of vehicles and increasing traffic complexity, the development of Intelligent Transportation Systems (ITS) has become essential in managing traffic flow, reducing congestion, and improving road safety. As a result, numerous research initiatives and projects have been launched in recent years in the Middle East and North African (MENA) countries. This paper presents a comprehensive review of the ITS projects funded in this region. We then evaluate these projects based on three criteria: security and data privacy, data analysis, and sensing techniques. The main objective is to identify common threads among these projects and explore potential opportunities for developing an open-source platform that can benefit the research community in the MENA region with similar research objectives.

Unmanned Aerial Systems (UASs) or drones are becoming increasingly dependable tools for many civil and industrial applications. Due to the increasing usage and capabilities of drones coupled with advances in innovative technologies and algorithms for managing and conducting tasks, drones are expected to crowd low-altitude airspace in urban areas. This brings many opportunities for service providers to provide drone-related services. Hence, efficient use of drones is required. In this paper, we investigate the benefits of reconfigurable softwarized drones operated by an entity or a service provider to perform tasks for its operations or for interested customers. We model a system of reconfigurable drones that can conduct multiple tasks per flight using Virtual Network Functions (VNFs) running on on-board capable computing systems. We compare our proposed model with alternatives with limited and no softwarization capabilities. Our evaluation demonstrates the performance gains due to reconfigurability in softwarized drone networks. Results show that softwarization allows drones to perform a variety of tasks using a limited number of reconfigurable drones and in a shorter time.

With the popularity of mobile edge computing (MEC), video streaming's peer-offloading strategy significantly affects the Quality of Experience (QoE) performance of video streaming for mobile users (MUs). Improving the service quality regarding the MUs' demand has become a vital challenge, reflected by QoE. This paper proposes a QoE-aware MEC-based peer-offloading method for HAS-based video streaming, called QOMECS. The proposed method considers dynamic MUs' demands and corresponding QoE requirements. We categorize the QoE KPIs into perceptual and systemic sectors. We formulate the corresponding transmission, computation, and offloading for MEC-based HAS into a QoE maximization problem. We propose a reverse-fuzzied particle swarm optimization (R-FPSO), to solve the highly nonlinear and perceptual-oriented optimization formulation. Unlike conventional fuzzy logic, R-FPSO reverses the fuzzification process by fuzzifying PSO's output (i.e. translated QoE KPIs into satisfactory levels) and further updates the particle values and velocities in the PSO process. Simulation results show that the proposed QOMECS dramatically improves the edge computing efficiency, with optimized QoE performance.

The emerging use of drones to support communication infrastructure and to deploy temporary networks in emergency scenarios is under active research. In this paper, we consider virtualizing drones' computing resources when deploying drone networks by utilizing Virtual Network Functions (VNFs) to process and deliver mission-related data traffic. This is aimed at cases where off loading and processing traffic to the cloud is not an option due to the unavailability of terrestrial and satellite communications. After discussing possible applications, we propose and evaluate a scheme for the deployment and placement of a drone network as well as the VNFs needed to deliver a set of traffics flowing from different locations in the task area.

This paper presents an improved algorithm for small cell (SCs) deployment in the heterogeneous network (HetNet) future generations of mobile networks. The sequential and fixed number of the SCs deployment is formulated as a joint optimization of load balancing and interference (JOLBI) minimization over the number and locations of the distributed user equipment (UE) forming a hotspot (HS). Then, the SCs are adaptively powered ON or OFF according to outcomes of the proposed clustering algorithms applied to the UEs' distribution. The conceived integrated solution of the JOBLI and clustering algorithm does not only satisfy the coverage constraint and maximize the minimum user throughput of the HetNet, but also enables an energy effective SCs deployment. The simulation results show that this JOLBI and clustering algorithm enables a power saving of the whole network by 35% when HS of UEs are considered in the network simulations.

As a new network architecture, Information-Centric Networks (ICN) has great advantages in content distribution and can better meet our needs. But it faced with many threats unavoidably. There are four types of attack in ICN: naming related attacks, routing related attacks, caching related attacks and miscellaneous attacks. These attacks will undermine the availability of ICN, the confidentiality and privacy of data. In addition, routers store a large amount of content for the users' request, and it is necessary to protect these intermediate nodes. Since the styles of content stored in nodes are not the same, using a unified set of intrusion detection rules simply will cause a large number of false positives and false negatives. Therefore, every node should perform intrusion detection according to its own characteristics. In this paper, we propose an intrusion detection mechanism to alert for abnormal packets. We introduce a extensive solution using machine learning for attacks in ICN. Moreover, the nodes in this scheme can adapt to the external environment and intelligently detect packets. Simulation on the machine learning algorithm involved prove that the algorithm is effective and suitable for network packets.

Controller placement is one of the most important aspects in Software Defined Networking (SDN) as it is critical in determining the performance of the network. While SDN is mainly applied in wired networks, we attempt to utilize it in a futuristic drone-based network architecture to capitalize on the programmability and flexibility offered by SDN. Such drone network comprises a multi-hop network of drones as the nodes of the network which also act as programmable network nodes and forwarding elements. In such a dynamic and mobile network, maintaining SDN controller connectivity becomes a challenge, especially when the drone network requires operating independently from a ground infrastructure for some deployment scenarios. In this work, we attempt to address this challenge by implementing a dynamic scheme for controller placement that deploys a minimum number of drones that operate as SDN controllers and adjust their locations dynamically as the controlled nodes adjust their locations to meet changing mission requirements.

Drones or Unmanned Aerial Vehicles (UAVs) are utilized in a wide range of applications, as they are considered flexible and cost-effective. Novel applications have been recently explored, such as providing communications and Internet coverage where ground infrastructure is lacking or in temporary situations. In this paper, we propose a drone-based network architecture enabled by Software Defined Networking (SDN) to provide dynamic and flexible networking capabilities, suitable for different types of drone applications and deployments, while we discuss associated challenges related to SDN in done networks.

This paper presents the implementation of an intelligent home-based elderly patient monitoring system. Four patient's physiological parameters are being continuously monitored, namely, temperature, glucose, and 3D accelerometer and gyroscope data for fall detection. Contextual sensors are mounted across the home to observe the patient's surrounding environment such as temperature and humidity. All sensors, wearable and contextual, transmit their measured data to smart gateways (fog layer) via nRF communication protocol. At the fog layer, diverse functions are being carried out, from collected measurements transfer to health care providers for further processing and analysis via Internet (cloud layer), sending push notifications and reports to patient's mobile phone, to alerting ambulance or civil defence authorities in case of an emergency. To insure power autonomy and eliminate the need for frequent sensor node battery replacement, an efficient thermal energy harvesting system is developed. Associated with a boost converter, the thermal energy harvesting system is able to sustain 3.3 OCV leveraging a temperature difference of 20°C between patient's body and room temperature, while achieving an efficiency of 82.6%.

Mobile computing proved to be essential in today's cyber communications. However, entities in mobile computing are known of having limited energy, physical, and logical resources. This imposes various challenges that greatly affect communication quality and performance of those mobile entities, especially when applying computationally-intensive security measures that are essential for protecting the communication sessions. Therefore, it becomes vital to seek suitable security techniques that balance between the communication performance and the resource context of those mobile entities. In this paper, we introduce the use of external aiding entities to assist in securing communications between feature-limited and resource-challenged next-generation mobile entities. We start with outlining different resource aiding approaches that help in securing communications. Then we discuss, in brief, both the design criteria and directions for a security resource aider. We, in the end, outline some of the challenges toward using security resource aiding in mobile and next generation communications.

The Safe System approach to road safety emphasizes safety-by-design through ensuring safe vehicles, road networks, and road users. With a strong WHO/UN motivation, the approach is increasingly adopted worldwide. Considerations in Safe System, however, are largely made for the medium-to-long term. Our interest in this work is complement the approach with a short-to-medium term dynamic assessment of road safety. Towards this end, we introduce a novel application of Hidden Markov Models (HMMs) at the core of road safety assessment. We also demonstrate the use of the dynamic assessment in safety-based route planning.

The Safe System (SS) approach to road safety emphasizes safety‐by‐design through ensuring safe vehicles, road networks, and road users. With a strong motivation from the World Health Organization (WHO), this approach is increasingly adopted worldwide. Considerations in SS, however, are made for the medium‐to‐long term. Our interest in this work is to complement the approach with a short‐to‐medium term dynamic assessment of road safety. Toward this end, we introduce a novel, cost‐effective Internet of Things (IoT) architecture that facilitates the realization of a robust and dynamic computational core in assessing the safety of a road network and its elements. In doing so, we introduce a new, meaningful, and scalable metric for assessing road safety. We also showcase the use of machine learning in the design of the metric computation core through a novel application of Hidden Markov Models (HMMs). Finally, the impact of the proposed architecture is demonstrated through an application to safety‐based route planning.

This paper presents the design of an autonomous smart patient/home health monitoring system. Both patient physiological parameters as well as room conditions are being monitored continuously to insure patient safety. The sensors are connected on an IoT regime, where the collected data is wirelessly transferred to a nearby gateway which performs preliminary data analysis, commonly referred to as fog computing, to make sure emergency personnel and healthcare providers are notified in case patient being monitored is at risk. To achieve power autonomy three energy harvesting sources are proposed, namely, solar, RF and thermal. The design of RF energy harvesting system is demonstrated, where novel multiband antenna is fabricated as well as an efficient RF- DC rectifier achieving maximum efficiency of 84%. Finally, the sensor node is tested with different type of sensors and settings while being solely powered by a Photovoltaic (PV) solar cell.

Crowd management in urban settings has mostly relied on either classical, non-automated mechanisms or spontaneous notifications/alerts through social networks. Such management techniques are heavily marred by lack of comprehensive control, especially in terms of averting risks in a manner that ensures crowd safety and enables prompt emergency response. In this paper, we propose a Markov Decision Process Scheme MDP to realize a smart infrastructure that is directly aimed at crowd management. A key emphasis of the scheme is a robust and reliable scalability that provides sufficient flexibility to manage a mixed crowd (i.e., pedestrian, cyclers, manned vehicles and unmanned vehicles). The infrastructure also spans various population settings (e.g., roads, buildings, game arenas, etc.). To realize a reliable and scalable crowd management scheme, the classical MDP is decomposed into Local MDPs with smaller action-state spaces. Preliminarily results show that the MDP decomposition can reduce the system global cost and facilitate fast convergence to local near-optimal solution for each L-MDP.

Advances in the Internet of Things (IoT) infrastructures are enabling the gathering, processing and inference of a wide array of data, enabling more agile decision management frameworks in several contexts, including vehicle routing and navigation. Coupled with crowd-sensing, these decision management frameworks gain further advantage in terms of data availability. This work concerns itself with safety in vehicle routing given different data modes. Specifically, we consider the design of an IoT framework for smart cities that facilitates robust safety-based routing for vehicles.

In this paper, we propose a novel deferred acceptance based resource allocation algorithm (DARA) for allocating LTE cellular user resource to D2D devices. The quality of service (QoS) constrained downlink resource block (RB) allocation problem is first formulated as a computationally expensive mixed integer nonlinear programming (MINLP) problem. We also propose a polynomial-time matching algorithm based on deferred acceptance method to find an allocation of cellular resources to D2D devices. Outcome of this algorithm is a stable matching of cellular users to the D2D devices. We compare the system sum rate obtained from DARA to that from a simple local search based algorithm (SLOC), a greedy heuristic based resource allocation algorithm (GHRA) and a random resource allocation algorithm. The simulation results show that, DARA achieves significantly better system sum rate than the rest of the algorithms while it runs in O(n2) in the worst case and O(n log n) on average.

Interference coordination while sharing cellular radio resources with Device-to-Device (D2D) pairs needs to be done in the short LTE scheduling period of 1 ms. In this paper, we propose a fast, two-phase auction based, fair and interference aware resource allocation algorithm (TAFIRA) for underlaying D2D communication. TAFIRA can be used to minimize the interference both at the evolved Node B (eNB) and the receiver of the D2D pairs while simultaneously maintaining a target system sum rate and ensuring fair allocation of cellular resources among D2D pairs. We compare TAFIRA with a MInimum Knapsack based Interference Resource Allocation algorithm (MIKIRA) and a random allocation technique. The time complexity of TAFIRA on average is O(m2n), where m and n are the number of D2D pairs and number of cellular users respectively. Our simulation results how that, TAFIRA obtains a much better system sum rate while incurring very little increased interference at the eNB and the D2D receivers when compared with MIKIRA and the random approach. TAFIRA also shows much more fairness in allocating cellular resources among the D2D pairs when compared with MIKIRA.

Mobile computing proved to be essential in today's cyber communications. However, entities in mobile computing are known of having limited energy, physical, and logical resources. This imposes various challenges that greatly affect communication quality and performance of those mobile entities, especially when applying computationally-intensive security measures that are essential for protecting the communication sessions. Therefore, it becomes vital to seek suitable security techniques that balance between the communication performance and the resource context of those mobile entities. This paper investigates some possible options toward implementing an adaptive security measures that work with various mobile and next generation Internet entities. The paper basically studies the communication performance of mobile entities when security functions are running on them with and without operating adaptations. While the focus in this paper is about the Message Authentication Code group of security functions, the work can be generalized to include any resource-intensive security measures including both other cryptographic (such as encryption) and non-cryptographic measures (such as challenges).

Abstract Deployments over large geographical areas in the Internet of Things (IoT) pose a major challenge for single‐hop localization techniques, giving rise to applications of multi‐hop localizations. And while many proposals have been made on implementations for multi‐hop localization, a close understanding of its characteristics is yet to be established. Such an understanding is necessary, and is inevitable in extending the reliability of location based services in IoT. In this paper, we study the characteristics of multi‐hop localization and propose a new solution to enhance the performance of multi‐hop localization techniques. We first examine popular assumptions made in simulating multi‐hop localization techniques, and offer rectifications facilitating more realistic simulation models. We identify the introduced errors to follow the Gaussian distribution, and the estimated distance follows the Rayleigh distribution. We next use our simulation model to characterize the effect of the number of hops on localization in both dense and sparse deployments. We find that, contrary to common belief, it is better to use long hops in sparse deployments, while short hops are better in dense deployments – despite the traffic overhead. Finally, we propose a new solution that decreases and manages the overhead generated during the localization process. Copyright © 2016 John Wiley & Sons, Ltd.

Resource allocation for Device-to-Device (D2D) communication underlaying cellular network poses new challenges in terms of interference while at the same time provides increased system sum rate. In this paper, we propose a local search based resource allocation algorithm (LORA) for allocating resource blocks to D2D devices that are shared with Long Term Evolution (LTE) cellular users. We first formulate the problem of downlink resource block (RB) allocation to D2D users from cellular users as a computationally expensive mixed integer nonlinear programming (MINLP) problem. However, as the optimal solution of an MINLP can take exponential time to compute, we propose a local search based algorithm to compute a locally optimal solution based on an initial feasible solution. We compare the obtained system sum rate from this local search algorithm with a well-known greedy heuristic based resource allocation algorithm and a random resource allocation algorithm. The simulation results show that LORA achieves an overall better system sum rate compared to the other algorithms for RB allocation while maintaining the signal quality at the cellular users and the D2D receivers.

Road fatalities in Saudi Arabia are expected to reach an alarming rate of one death per hour in 2015. In this paper, we describe a framework for vehicular sensing that is directly aimed at instilling safe driving. The presented architecture utilizes access to vehicle's CAN-Bus through an OBD-II connector. The access is processed using both on-vehicle smartphone and in-the-cloud processing. Road conditions (e.g., potholes, speedbumps, slowdowns, etc.) are recognized and utilized to classify roads using a threshold-based engine. The proposed framework is designed with strong emphasis on extendability, and a service application providing drivers with Quailty of Road (QoR) status is demonstrated.

Sharing resources between Long Term Evolution (LTE) cellular users and Device-to-Device (D2D) pairs comes at the cost of increased interference. In this paper, we propose a Minimum Knapsack-based Interference-aware Resource Allocation (MIKIRA) approach to show that a channel sharing approach can be used to increase system sum rate, minimize the interference both at the evolved Node B (eNB) and the receiver of the D2D pairs, and most importantly achieve a good signal quality at the eNB in lower time complexity in an LTE cellular network. We compare the system sum rate, interference and Signal-to-Interference and Noise Ratio (SINR) obtained by MIKIRA with a bipartite graph-based approach (GRA) for resource allocation and a random allocation approach. ¿From the results we find that MIKIRA shows improved performance when compared to other approaches in all of the metrics we used in the simulation. MIKIRA is more efficient in terms of time complexity (O(n2log(n))) when compared with the GRA (O(n3)); and also results in higher quality signals as the SINR achieved at the eNB is much better than the other two approaches.

Abstract Towards satisfying the requirements of International Mobile Telecommunications–Advanced, both the Institute of Electrical and Electronics Engineers (IEEE) and Third Generation Partnership Project (3GPP) introduced revolutionary wireless technologies, exploiting advanced technologies and architectures. Both IEEE's 802.16 (Worldwide Interoperability for Microwave Access (WiMAX)) and 3GPP's Long Term Evolution have been introduced to accommodate the increasing demand for mobile services and applications. To realize the true potential of these technologies, however, opportunistic frameworks for radio resource management must be designed to exploit the adaptive nature of mobile traffic. The utility optimized quality‐of‐service (QoS) framework proposed in this paper for the mobile WiMAX networks achieves this objective. To maintain support for QoS guarantees, the framework capitalizes on the adaptive nature of WiMAX traffic by individually linking connections with a utility function designed to both uphold the end users’ perceived performance and determine bandwidth allocations by a search tree maximization algorithm. In doing so, bandwidth utilization is maximized for all active connections, and blocking and dropping probabilities for new and handover calls, respectively, are minimized. The framework is evaluated through an extensive simulation model and is shown to outperform state‐of‐the‐art solutions. Copyright © 2014 John Wiley & Sons, Ltd.

Estimating the location of sensor nodes in wireless sensor networks is a fundamental requirement in a variety of sensing applications. In large scale dense deployments where the area covered by sensor nodes is very large, it is impossible to localize all sensor nodes using single-hop localization techniques. A solution to this problem is to use a multi-hop localization technique to estimate sensor node positions. In some deployments it is required to maintain the anchor nodes at the edge of the simulated area. In previous work, we introduced a new localization scheme that uses distance measurements to localize sensor nodes using a collinear and non-collinear mobile anchor nodes placed at the edge of the sensed area. A Kalman Filter was then used to improve the location accuracy for each node. In this scheme each SN estimated its location from two independent directions then use such information to improve localization accuracy. In this paper, we extend the work to use side localization using hop measurements and fixed anchor node. We also compare the performance of using side localization for both hop and distance measurement. Through simulation we show that side localization using distance and hop measurements outperform DV-Hop and DV-Distance, which are mainstream localization protocols. The weighted mean hop measurement gives higher localization accuracy than using using distance measurement. However, if Kalman Filter is used distance measurement gives better localization accuracy.

Communication security measures are becoming prominent standards of next generation mobile networks. These measures usually involve resource-intensive cryptographic operations that can greatly affect communication performance, particularly when it comes to time-based guarantees such as delay and jitter. It this becomes vital to understand the computational characteristics of such operations from a communication perspective. The determination of these characteristics, however, is challenging with mobile computing as computational resources are dynamically managed for balanced performance and energy-efficiency. This paper investigates different mobile computing resource management features, and evaluates their impact on the evaluation of cryptographic functions used in message authentication, and on the design considerations for future context-aware security protocols.

Multi-standard mobile terminals (MTs) allow mobile users to experience ubiquitous connectivity and better quality of service. However, these advances come at a price of higher power consumption for MTs due to holding multiple active interfaces. In this paper, we apply multihop relaying through pervasive short range interfaces (e.g., Bluetooth, WiMedia. etc.) in the presence of an infrastructure network (e.g., LTE, WiFi, etc.) to extend the battery lifetime of multi-standard MTs. To this end, MTs exchange context information (conveying channel state information, battery level, etc.) and, whenever beneficial, form a coalition, pool their resources, and perform their tasks cooperatively to enhance their efficiency. We introduce a novel utility function to assess the profitability of cooperation. To incentivize MTs to cooperate, the achieved common utility of the coalition can be distributed among the cooperative MTs by means of energy credits using a solution concept from coalitional game theory. The simulation results validate the effectiveness of the proposed approach to extend the battery lifetime of MTs to more than double.

Femtocells play a critical role in LTE and LTE-Advanced networks. Their particular advantage is realized by their autonomy in management and optimization. Our interest in this work is in a special category of self-optimization use cases overseeing femtocell handovers. Specifically, we present a flexible, extendable and standards-compliant environment written in MATLAB for studying handover related self-optimization schemes. The paper describes the overall structure and design of the environment, and offers a detailed explanation of the different modules involved. Sample results that validate the environment are also given. To the best of our knowledge, no such environment has been publicly accessible so far.

A Self Organizing Network (SON) scheme monitors certain Key Performance Indicators (KPIs) and responds by adjusting system control parameters. Multiple SON schemes may have related KPIs or use the same control parameters. This leads these schemes and their use cases to interact either constructively or destructively. In this paper, we study these interactions between three SON use cases all aiming at improving the overall handover procedure in LTE femtocell networks. These use cases are namely: handover self optimization, call admission control self optimization and load balancing self optimization. This work is motivated by the lack of interaction studies conducted so far between these three self optimization use cases. First, we have surveyed related individual scheme proposals in order to identify schemes which represent these three use cases in our interaction study. Then, several interaction experiments are conducted in realistic scenarios using our in-house built and LTE-compliant simulation environment. We conclude by drawing guidelines that we believe can help designers realize better coordination policies between these three handover-related SON use cases.

The next-generation mobile networks will be equipped with sophisticated communication security, ensuring the safety and authenticity of the transmitted information. However, many of today's prominent security measures are cryptography-based and present several operational challenges in mobile computing systems. Thus, enforcing security measures can greatly affect communication performance, particularly, when it comes to time-based guarantees such as delay and jitter. Moreover, mobile computing systems have limited energy sources, which can be depleted quickly by improperly enforcing such resource-intensive operations. Therefore, it becomes vital to understand the computational characteristics of security measures from a communication perspective. By observing these characteristics, it may be possible for existing and future mobile systems to be suited with security functions that provide the sufficient communication security while maintaining both the power-efficiency and the delay/jitter requirements. In this paper, we propose a benchmarking environment for evaluating cryptography-based security functions from a communication perspective. The paper investigates how mobile systems' design and operation characteristics have a significant impact on the computational characteristics of security functions. The paper explores the evaluation metrics that can be used in benchmarking security functions within various communication settings and proposes the use of a simple and effective delay-based metric for the benchmarking process. The computational characteristics of some selected security functions are evaluated under the proposed benchmarking environment and presented in this paper. While the main focus of the work is the widely utilized mobile communication settings, the proposed evaluation scheme can be applied for other communication settings and for noncryptographic security functions.

Common Radio Resource Management techniques have shown great promise in both enhancing network operation and user satisfication.Such gains are achieved through the joint management of the individual access technologies in a Heterogeneous Wireless Network.The objective of this work is to expand on the existing body of work to accommodate heterogeneity not just at the traditional access-network level but to other connectivity modes such as dynamic spectrum access.Such modes affect operator profitability in both the long and short terms.Specifically, we explore the design of a cost-management model that adapts to the short-term variability in connectivity costs.We also display the operational aspects and effectiveness of this functionality through both simulation and an analytical model.

Estimating the location of sensor nodes in wireless sensor networks is a fundamental problem, as sensor node locations play a critical role in a variety of applications. In many cases the area covered is very large making it impossible to localize all sensor nodes using single-hop localization techniques. A solution to this problem is to use a multi-hop localization technique to estimate sensor node positions. Multi-hop localization techniques are classified into two main categories: range-based and range-free. Despite the numerous existing localization techniques, the fundamental behavior of multi-hop localization is yet to be fully examined. The aim of this paper is to study the effect of errors in a multi-hop localization environment and how this impacts localization accuracy. There has been a general belief that a fewer number of hops results in higher accuracy. Through different experiments on two generic localization techniques representing both categories of localization schemes, we show that such belief is not true in all cases, as in dense environments often using shorter hops gives better accuracy.

Knowing the position of sensor nodes in an environmental monitoring is useful to identify the location of events. However deploying GPS receivers or other anchor sensors is expensive, since the role of anchor nodes ends after localizing sensor nodes' positions and they are transferred into ordinary sensor nodes. In this paper, we introduce a new localization scheme for a wireless sensor network that can localize sensor nodes using a collinear and non-collinear mobile anchor node. This scheme benefits from the estimated distance between neighbor nodes and additional information provided by the anchor node about the flow direction of the message. Each node localizes it's position from two independent directions. A Kalman Filter is then used to improve the location accuracy for each node. Through simulation studies, we show that the scheme using a Kalman Filter decreases the estimation errors than using single direction by 31% and 16% better than using weighted averages. As well, our new scheme overcomes the collinearity problem that appears from using mobile anchor nodes.

SUMMARY This paper evaluates the effect of the choice of frame structure type in WiMAX networks employing non‐transparent relay stations (ntRS). The IEEE 802.16j‐2009 amendment allows two frame structure types, single frame and multiframe. Thus far, a comparison of the two choices, in terms of network performance, has not been made. To facilitate this evaluation, we expanded on light WiMAX ns2 add‐on to support ntRS, the two‐frame structure types, in addition to the relevant operational requirements (e.g. QoS support). We observed that whereas the multi‐frame structure allows for higher throughput and voice capacities, the single frame shows some general advantage in terms of delay. A serious need exists, however, for schedulers that exploit the advantages of a dynamic multi‐frame structure in order to realize its full potential. Copyright © 2011 John Wiley & Sons, Ltd.

With the increased popularity of both Internet and mobile computing, several security mechanisms, each using various cryptography functions, have been proposed to ensure that future generation Internets will guarantee both authenticity and data integrity. These functions are usually computationally intensive resulting in large communication delays and energy consumption for the power-limited mobile systems. The functions are also implemented in variety of ways with different resource demands, and may run differently depending on platform. Since communications within the next generation Internet are to be secured, it is important for a mobile system to be suited to the function that provide sufficient communication security while maintaining both power-efficiency and delay requirements. This paper benchmarks mobile systems with cryptographic functions used in message authentication. This paper also introduces a metric, namely apparent processing, that makes benchmarking meaningful for mobile systems with multiple processing cores or utilizing hardware-based cryptography. In addition, this paper discusses some of evaluated functions' computational characteristics observed through benchmarking on selected mobile computing architectures.

In this paper we present a joint resource allocation and optimal relay selection scheme that meets the data rate QoS requirement of traffic in OFDMA networks. The proposed scheme selects the relay that best utilizes the attainable data rate for all subcarriers, as opposed to existing works which are based on selecting the optimal relay independently per single subcarrier. The scheme is further designed as a finite horizon Markov Decision Process (MDP). Simulation results show that the proposed scheme outperforms representative existing schemes in terms of the network total throughput and end-to-end outage probability.

Increasing attention and effort has recently been invested in reducing the energy requirements of wireless communication networks. Such increase is readily justified by the reduction of non-renewable resources, in addition to continuously expanding popularity of wireless data traffic, especially high fidelity transfers. The intent of this paper is to offer a perspective on green wireless networks from the point of view of Radio Resource Management (RRM) design. This paper reviews basic preliminaries prior to detailing the essential RRM challenge how to best allocate the available resource. It then expands on such considerations in view of the search for “green” answer. In doing so, the paper highlights the limitations and trade-offs affecting design efficiency, and concludes with identifying critical concerns in the methods used for validating energy reduction proposals.

3GPP's Long Term Evolution is defined by the standardization body's Release 8 and 9, and provides more than a substrate for 3GPP's IMT-Advanced candidate, namely LTE-Advanced, which is due to be defined in Release 10. Both LTE and LTE-Advanced have SC-FDMA in their uplink, a multi-carrier access technique requiring contiguous subcarriers allocations for each UE. No scheduling algorithm, however, is dictated by the standard and several proposals have hence been presented to implemented by vendors. A definite scheduling requirement is the support of QoS attributes of different types of uplink traffic. Our intent in this study is evaluate the connection-level performance of representative scheduling proposals, with focus on QoS aspects. Specifically, we utilize a mixed type of traffic flows and evaluate the schedulers in terms of per-user throughput, delay, packet loss and fairness.

Distribution of radio resources in fourth generation (4G) networks requires sophisticated Radio Resources Management (RRM) techniques to guarantee a sustainable level of Quality of Service (QoS) support. By analyzing the adaptive nature of the project applications and their traffic it is possible to substantially enhance broadband service delivery. In this paper, we propose a Utility Optimized QoS (UOQoS) scheme for mobile WiMAX. The scheme maintains a high level of QoS support by maximizing bandwidth utilization and minimizing the rejection of both new and handover calls. It takes advantage of the adaptive nature of WiMAX traffic by associating each connection with a unique and appropriate utility function. The performance of the UOQoS is validation through simulation.

Localization will play an important role in the Internet of Things (IoT), and will employ several complementary mechanisms, each applicable to Things with different characteristics. This paper investigates the impact of scale and mobility on wireless multi-hop localization mechanisms, which specifically target Things with limited capabilities inhibiting them for self- localization, i.e., cannot locally perform trilateration or angle of arrival analysis. Building on a representative system for wireless multi-hop localization, we evaluate the impact of network size and node mobility on various operational aspects, including number of messages sent, collisions, localization accuracy, in addition to the percentage of unlocalized nodes. We also show how a basic optimization can result in substantial gains. More critically, however, we establish the need for further optimizations in realizing localizations in IoT.

Remote monitoring systems employing a Wireless Body Area Network (WBAN) require a capable and efficient connectivity between the WBAN and other system components overseeing personal and autonomous monitoring and processing of the gathered data. The requirements for remote monitoring applications, however, challenge existing connectivity technologies. Towards this end, the characteristics of the next generation wireless broadband systems meeting the requirements of ITU's IMT-Advanced systems seem promising. The objective of this article is to review how IMT-Advanced systems will accommodate the requirements for remote monitoring applications, together with the technologies facilitating this accommodation.

The choice of SC-FDMA for uplink access in Long Term Evolution (LTE) facilitates great flexibility in allocating medium resources to users while adapting to medium condition. A multicarrier multiple access technique, SC-FDMA gains an advantage over OFDMA in that it reduces the energy requirements in user equipment. 3GPP Releases 8 and 9, however, do not detail a specific scheduler and, accordingly, proposals have been made in the literature in designing an efficient and capable uplink scheduler for LTE. This paper presents a preliminary performance evaluation for representative proposals, and offers medium of comparison in order to highlight the individual characteristics of each proposals.

This study evaluates the effect of the choice of frame structure type in WiMax networks employing non-transparent relay stations (ntRS). The IEEE 802.16j–2009 amendment allows two frame structure types, single frame and multi frame. Thus far, a comparison of the two choices, in terms of network performance, has not been made. To facilitate this evaluation, we expand on Light WiMax (LWX) ns2 add-on to support ntRS, the two frame structure types, in addition to the relevant operational requirements (e.g. QoS support). We observe that while the multi-frame structure allows for higher throughput and voice capacities, the single frame shows some general advantage in terms of delay.

Welcome to the WLN 2009, taking place in Zurich, Switzerland!

Capitalizing on the unifying capabilities of IP, future wireless network operators (WNO) will be able to deploy heterogeneous wireless networks (HWNs). The heterogeneity will enable users to continuously connect to the technology that best meets the users' application requirements. It will also allow WNOs to change the associations of users to attain certain operational objectives. Despite the possible employment of cost reduction mechanisms based on long term observations, we argue that the user-centric nature of HWNs and the possible permutations of triggers for vertical handoffs (VHs) may effectively render user assignment beyond the WNO's control. In this paper, investigate the potential of a module dedicated to reduce the cost of service delivery. In doing so, we discuss the considerations of such a module, including the factors affecting the cost of service delivery and the elements involved in identifying and selecting users to undergo a forced VH.

Tag collisions can impose a major inefficiency in RFID systems, resulting in low identification rates, short reading range and ineffective resource utilization. They are more problematic in passive tags due to limitations on power and functionality. In this paper, we present a novel approach to overcome the passive tag collision problem. The novelty in our scheme is that it requires no additional memory, results in a higher identification rate and reduces power and medium consumption. The proposed scheme can be augmented to tree- based anti-collision proposals, both existing and to come, and substantially improve their performance. Performance results indicate that the augmented schemes bear significant gains that are achieved by reducing collision, overhead and delay.

The IP multimedia subsystem (IMS) provides a framework that accommodates current and future services in wired and wireless networks. However, IMS does not handle non-3G elements such as wireless local area networks (WLANs). In order to provide interconnection at the service layer between 3G and WLANs, interworking between IMS and WLAN is necessary. Extending IMS beyond 3G to WLANs is a crucial step towards the evolution of a seamless universal next generation wireless network, commonly known as 4G. In this paper, a novel architecture for service layer interworking between WLAN and 3G is presented. The architecture takes into consideration the interaction of WLAN Application SIP servers with the IMS call session control functions (CSCFs) and the extensibility of application servers (ASs) beyond the core IMS network. A WLAN AS is introduced into the IMS network and an SIP server into the WLAN. These act as interworking arbitrators and communicate with each other to provide service and session continuity. The main advantage of this architecture is its feasibility within the standard. It is also non-intrusive to the IMS core or the WLAN.

Vertical Handoffs occur when a user changes association from one type of wireless access technology to another while maintaining an active session. Much work has been done in ensuring seamless handoffs that also preserve QoS. However, service providers can exploit vertical handoffs as a Radio Resource Management (RRM) means to relieve congestion, load balance and uphold QoS requirements. Nevertheless, this exploitation requires rigorous study in order to realize its full potential. In this paper, we advocate the use and study of forced vertical handoffs as a powerful RRM tool. We also discuss the different factors involved in the design and operation a forced vertical handoff module (FVHM). Furthermore, we provide a RRM framework for future wireless network where an FVHM is employed and set to interact with a bandwidth adaptation algorithm. In the framework, we introduce the Willingness function, a novel representation for a user's instantaneous willingness to undergo a forced vertical handoff.

Much of the literature have mainly investigated the seamlessness and the effects of Vertical Handoffs (VHs), in addition to the design of policy-based Radio Resource Management (RRM) models that cater for their unique characteristics. However, VHs can be viewed as a powerful RRM tool. A service provider may force users to handoff to other networks in a coverage overlay to relieve congestion or balance the load. In this paper, we present a novel multi-class, subadaptation module for forced vertical handoffs. We discuss added arguments required by the multi-class setting, and show the flexibility of our model through its capability to meet different objectives for different service providers.

In this paper, we outline the basis of a novel cooperative module for congestion control and load balancing in WCDMA networks. Through carefully exploiting the capabilities of smart and directional antennas, we propose a controllable directional breathing where a base station's (BS) sectorized coverage is varied reactively in instances of congestion, and proactively in instances of exercising load balancing. This proposal, called Directional Cell Breathing (DCB), overcomes the drawbacks of non-sectorized and non-controllable WCDMA breathing management by optimizing the coverage level within each sector under constraints minding sectoral traffic load and interference bounds. Interference analysis is carried out to determine the eligibility of a cell to be considered in DCB if one of its adjacent cells becomes overloaded. This analysis is then used in a mathematical formulation to facilitate the optimization of the proposed scheme.

Bandwidth adaptation algorithms (BAA) assume an integral role in radio resource management (RRM) frameworks for future wireless networks. Taking advantage of the nature of adaptive multimedia application, they empower system providers with allocation versatility and economic increase. Due to the dynamic nature to be witnessed in future networks, BAA has been set to be trigger at every change in the system state. This burdens the different entities involved in RRM. In this work, the concept of stochastically triggered BAA (STBAA) is proposed. The tradeoff between admission ratios and users satisfaction is evaluated. It is found that considerable gains can still be achieved with the adaptation not fully engaged

The introduction of wireless multimedia applications brought about an attractive characteristic from a resource management point of view, namely the adaptability of such applications. Allocations made to deliver the multimedia applications can be varied depending on the conditions of the user, the network, or both. In a framework for resource management, the role of a bandwidth adaptation algorithm (BAA) is to provision the adaptation of the different users in A cell. Previous proposals for BAA persistently engage the adaptation whenever required. Naturally, this comes at a high system cost. In this work, the novel notion of stochastically triggered bandwidth adaptation algorithms (STBAA) is introduced. The objective of the STBAA framework is to allow system providers to exploit the tradeoff between admission ratios and user satisfaction in order to control the operational cost of adaptation.

A vertical handoff describes the event when a mobile terminal changes its association from one type of wireless access technology to another, whether or not the networks involved belong to one provider. Of the many intricacies yet to be understood in heterogeneous wireless networks is the exact effect of vertical handoffs due to different triggers. In this paper, an attempt is made to dichotomize the interaction of preference-triggered vertical handoffs and joint allocation policies. A general framework for evaluating allocation policies in heterogeneous environments is described. Models for disjoint and joint resource management are developed. Adequate admission control policies are also presented. It is found that, even though a joint allocation policy does enhance service delivery to new-call requests, handoff-call requests may undergo slight negative effects.

In fourth generation (4G) wireless networks, users are able to roam freely from one type of wireless access network to another while preserving the main characteristics of their connections. While various aspects of this vision have been discussed since mid 1990s, there remain fundamental challenges. Of these challenges is performing resource management across different access networks while considering various irregularities. This work advocates that any proposal for resource management in such networks should act reactively toward operational dynamicity while proactively allocating resources in a manner that sustains demand uncertainty. It shows how proactive allocations can be made using a formulation based on stochastic programming. The objective is to maximize the allocations while minimizing underutilization and rejection. It also discusses how a comprehensive proactive module can be realized. To the best of our knowledge, this is the first attempt to directly address joint resource management in wireless heterogeneous networks.