A swarm of unmanned aerial vehicles (UAVs) is a wireless network made up of UAVs cooperating to upload data to the internet. During critical scenarios like earthquakes, one or more UAV could get damaged. Clustering is one of the most dependable routing systems since the network is divided into clusters with a cluster head (CH) and cluster members (CM). Having a damaged CH results in a disconnected cluster and loss of valuable data. Ensuring a functional CH is a crucial topic that is rarely covered in routing schemes. Our proposed scheme targets ensuring a functional CH through multiple redundancies while redeucing the delays. This paper suggests an enhanced redundant routing scheme based on three weighted parameters, which are the distance stability, the rewarding stability, and the energy stability. The weighted calculation will result in a new metric named cluster index which will be utilized in CH and CMs selection. To guarantee connection stability, whenever the primary CH is not operating, a redundant CH handles the routing responsibilities. The proposed protocol was simulated using MATLAB. The results obtained demonstrated that our proposed scheme is promising in optimizing the cluster formation while reducing total delays and ensuring a functional CH and data delivery.

A UAV-based wireless network is made up of UAVs working together to upload data to the internet. During crisis scenarios like earthquakes or floods, UAVs are highly used in transmitting valuable health-related data. Basic physiological life-saving parameters like blood pressure, temperature, and respiration rate can be tracked by sensors built into UAVs. One of the most reliable routing techniques in UAVs is clustering, where the network is separated into clusters, each of which has a cluster head (CH) and cluster members (CM). Having a damaged CH results in a disconnected cluster and loss of data. Several routing schemes target reducing delays, but ensuring a functional CH is a topic rarely discussed. Our proposed scheme targets both reducing delays and ensuring a functional$\mathbf{C H}$through multiple redundancy and node type variation to ensure health data transmission. This paper suggests an enhanced redundant routing scheme based on four weighted parameters, which are the distance stability, the rewarding stability, the velocity stability, and the energy stability. The network will be formed of UAVs and vehicles to maximize the likelihood of a functional$\mathbf{C H}$. The weighted calculation will result in a customized metric utilized in cluster formation. To guarantee connection stability, whenever the primary$\mathbf{C H}$is not operating, a redundant$\mathbf{C H}$handles the routing responsibilities. The proposed protocol was simulated using MATLAB. The results obtained demonstrated that our proposed scheme is promising in optimizing the cluster formation while reducing total delays and ensuring a functional CH.

Swarm of UAVs (S-UAVs) is the term used to describe an unplanned gathering of un-manned aerial vehicles (UAVs) that collaborate to complete predefined missions. Any UAV has a risk of being damaged in crisis situations like fire. Clustering is one of the most often used routing algorithms in S-UAVs. The clustering scheme divides the UAVs into clusters, with a cluster head (CH) and cluster members (CM) in each cluster. The CH plays a critical role within inter-cluster communication, and because of this, its selection is an ongoing area of study. A clustered weighted scheme with redundancy and dynamic weight adjustment is proposed in this paper. The selection of the principal CH, redundant CHs, and CMs is based on a weighted formula composed of distance, speed, and rewarding index. Whenever the primary CH is damaged, the redundant CH takes its place immediately. After the first clustering process, the proposed scheme dynamically and autonomously adjusts the weights to optimize the UAV role selection. According to the outcomes of the carried-out simulation, this is a promising scheme that reduces data loss in a crisis-case scenario and optimizes the time delay through the dynamic adjustments of the weights.

A swarm of unmanned aerial vehicles (S-UAVs) consists of UAVs flying together with the target of accomplishing a certain task in a faster and more reliable way as compared to a single UAV. In a crisis scenario, UAVs have been widely used in rescue missions. Clustering is one of the most reliable routing schemes for S-UAVs. The UAVs are grouped into clusters with a cluster-head (CH) and cluster-members (CM). The CH plays a major role in clustering schemes as it handles all inter-cluster communication. In a crisis case, any UAV is at risk of getting non-functional, thus resulting in a disconnected cluster. This paper proposes a new clustering scheme based on K-means and weighted formulas. The K-means protocol is applied to generate pilot phase clusters. Afterward, whenever the metrics of the networks are established, the weighted formula is applied for cluster formation and CH selection. The weighted formula is based on the performance index, the relative movement, and the remaining energy. To ensure end-to-end communication despite CH non-functionality, our proposed protocol selects a redundant CH for every CH. This protocol had been simulated using MATLAB. The results obtained and analyzed towards the end of this paper demonstrate that the proposed scheme is very promising.

A spontaneous group of unmanned aerial vehicles (UAVs) is denoted as a swarm of UAVs (S-UAVs). The UAVs communicate wirelessly and cooperate to accomplish tasks. In crisis scenarios such as flooding or earthquakes, all UAVs are at risk of getting damaged and thus non-functional. A non- functional UAV will result in a disconnected network, especially if that UAV is highly responsible for packet forwarding. S- UAV s are dynamic networks; clustering is one of the most adopted routing schemes in S-UAVs. The clustering scheme groups the UAVs into clusters where each cluster is formed of a cluster head (CH) and cluster members (CMs). Only the CH can handle inter-cluster communication. Due to the crucial role played by the CH, its selection is a continuous field of research. This paper proposes an enhanced clustered weighted scheme with redundancy to ensure end-to-end communication. The proposed scheme is based on a weighted formula for the primary CH, redundant CH, and CMs selection. The weighted formula calculates a cluster index based on the distance, the speed, and the reward index. A new component is added to the reward index which is performance. The redundant CH is selected to automatically replace the primary CH whenever it is damaged. If the redundant CH becomes inoperable, the second redundant CH will take over. Each cluster is formed of n CMs and will have n-2 redundant CHs. The results obtained from the conducted simulation experiments concluded that this promising scheme decreases data loss in a crisis case scenario.

This article proposes a user-adaptable and personalized authentication paradigm for healthcare organizations, which anticipates to seamlessly reflect patients’ episodic and autobiographical memories to graphical and textual passwords aiming to improve the security strength of user-selected passwords and provide a positive user experience. We report on a longitudinal study that spanned over 3 years in which three public European healthcare organizations participated to design and evaluate the aforementioned paradigm. Three studies were conducted ( n = 169) with different stakeholders: (1) a verification study aiming to identify existing authentication practices of the three healthcare organizations with diverse stakeholders ( n = 9), (2) a patient-centric feasibility study during which users interacted with the proposed authentication system ( n = 68), and (3) a human guessing attack study focusing on vulnerabilities among people sharing common experiences within location-aware images used for graphical passwords ( n = 92). Results revealed that the suggested paradigm scored high with regard to users’ likeability, perceived security, usability, and trust, but more importantly it assists the creation of more secure passwords. On the downside, the suggested paradigm introduces password guessing vulnerabilities by individuals sharing common experiences with the end users. Findings are expected to scaffold the design of more patient-centric knowledge-based authentication mechanisms within today's dynamic computation realms.

Reconfigurable Intelligent Surfaces (RIS) are well established as a promising solution to the blockage problem in millimeter-wave (mm-wave) and terahertz (THz) communications, envisioned to serve demanding networking applications, such as 6G and vehicular. HyperSurfaces (HSF) is a revolutionary enabling technology for RIS, complementing Software Defined Metasurfaces (SDM) with an embedded network of controllers to enhance intelligence and autonomous operation in wireless networks. In this work, we consider feedback-based autonomous reconfiguration of the HSF controller states to establish a reliable communication channel between a transmitter and a receiver via programmable reflection on the HSF when Line-of-sight (LoS) between them is absent. The problem is to regulate the angle of reflection on the metasurface such that the power at the receiver is maximized. Extremum Seeking Control (ESC) is employed with the control signals generated mapped into appropriate metasurface coding signals which are communicated to the controllers via the embedded controller network (CN). This information dissemination process incurs delays which can compromise the stability of the feedback system and are thus accounted for in the performance evaluation. Extensive simulation results demonstrate the effectiveness of the proposed method to maximize the power at the receiver within a reasonable time even when the latter is mobile. The spatiotemporal nature of the traffic for different sampling periods is also characterized.

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.

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.

Metasurfaces constitute a revolutionary technology for the realization of intelligent reflecting surfaces (IRS) which can alleviate the blockage problem in mmWave and Thz communications in the absence of Line of Sight (LOS). In this work, we consider the use of multiple IRSs to provide LOS paths between a sender and a receiver via reflection. Unlike previous work, we use the directivity as a means to incorporate the metasurface reflection behavior in the channel model and parameterize with respect to the design parameters. The design problem considered is the choice of the “best” IRSs for consecutive reflection of the transmitted signal to optimize the communication channel. The problem is formulated as an optimization problem which is challenging to solve due to the dependence of each link cost on the previous link. We consider a relaxation which decouples the link costs, we apply Dijkstra’s algorithm for the solution and we show that the performance degradation as compared to the original problem which is solved using exhaustive search is not significant.

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.

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.

In this paper, we propose an eye gaze-driven metric based on hotspot vs. non-hotspot segments of images for unobtrusively estimating the strength of user-created graphical passwords by analyzing the users' eye gaze behavior during password creation. To examine the feasibility of this method, i.e., the existence of correlation between the proposed metric and the strength of users' generated passwords, we conducted an eye-tracking study (n=42), in which users created a graphical password with a personalized image that triggers declarative memory of users (familiar image) vs. an image illustrating generic content unfamiliar to the users' episodic and semantic memory (generic image). Results revealed a strong positive correlation between the password strength and the proposed eye gaze-driven metric, pointing towards a new direction for the design of intelligent eye gaze-driven graphical password schemes for unobtrusively assisting users in making better password choices.

The Second International Workshop on Adaptive and Personalized Privacy and Security (APPS 2020) aims to bring together researchers and practitioners working on diverse topics related to understanding and improving the usability of privacy and security software and systems, by applying user modeling, adaptation and personalization principles. Our special focus in 2020 is on healthcare systems, more specifically on ensuring security and privacy of medical data in smart patient-centric healthcare systems. The second edition of the workshop includes interdisciplinary contributions from Austria, Canada, China, Cyprus, Denmark, Germany, Greece, Israel, the Netherlands, Turkey and the UK that introduce new and disruptive ideas, suggest novel solutions, and present research results about various aspects (theory, applications, tools) for bringing user modeling, adaptation and personalization principles into privacy and systems security. This summary gives a brief overview of APPS 2020, held online in conjunction with the 28th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP 2020).

Picture passwords, which require users to draw selections on images as their secret password, typically provide globalized solutions without taking into consideration that people across diverse cultures exhibit differences within interactive systems. Aiming to shed light on the effects of culture towards users' interactions within picture password schemes, we conducted a between-subjects cross-cultural (Eastern vs. Western) study (n=67). Users created a password on a picture illustrating content highly related to their daily-life experiences (culture-internal) vs. a picture illustrating the same daily-life experiences, but in a different cultural context (culture-external). Results revealed that people across cultures exhibited differences in visual processing, comprehension, and exploration of the picture content prior to making their password selections. The observed differences can be accounted by considering sociocultural theories highlighting the holistic preference of Eastern populations compared to the analytic preference of Western populations. Qualitative data also triangulate the findings by exposing the likeability and users' engagement towards the picture content familiar to individual's culture. Findings underpin the necessity to consider cultural differences in the design of personalized picture passwords.

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.

Future-generation healthcare systems will be highly distributed, combining centralised hospital systems with decentralised home-, work-and environment-based monitoring and diagnostics systems. These will reduce costs and injury-related risks whilst both improving quality of service, and reducing the response time for diagnostics and treatments made available to patients. To make this vision possible, medical data must be accessed and shared over a variety of mediums including untrusted networks. In this paper, we present the design and initial implementation of the SERUMS tool-chain for accessing, storing, communicating and analysing highly confidential medical data in a safe, secure and privacy-preserving way. In addition, we describe a data fabrication framework for generating large volumes of synthetic but realistic data, that is used in the design and evaluation of the tool-chain. We demonstrate the present version of our technique on a use case derived from the Edinburgh Cancer Centre, NHS Lothian, where information about the effects of chemotherapy treatments on cancer patients is collected from different distributed databases, analysed and adapted to improve ongoing treatments.

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.

Graphical passwords leverage the picture superiority effect to enhance memorability, and reflect today's haptic users' interaction realms. Images related to users' past sociocultural experiences (e.g., retrospective) enable the creation of memorable and secure passwords, while randomly system-assigned images (e.g., generic) lead to easy-to-predict hotspot regions within graphical password schemes. What remains rather unexplored is whether the image type could be inferred during the password creation. In this work, we present a between-subjects user study in which 37 participants completed a recall-based graphical password creation task with retrospective and generic images, while we were capturing their visual behavior. We found that the image type can be inferred within a few seconds in real-time. User adaptive mechanisms might benefit from our work's findings, by providing users early feedback whether they are moving towards the creation of a weak graphical password.

Graphical passwords leverage the picture superiority effect to enhance memorability, and reflect today's haptic user interaction realms. Image content related to users’ past sociocultural experiences assists users with the creation of more secure and memorable passwords. Aiming to shed light on the effects of sociocultural-related image content towards graphical password selections, we conducted a between-subjects eye-tracking study (N=37) in which users selected one image among a set of images from their assigned image group (sociocultural-related vs. generic) that would be used for creating their graphical password. Results revealed differences in users’ interaction and visual behavior during image selection. Initial users’ feedback regarding the likeability and users’ engagement with the sociocultural-related image content is also presented.

Probabilistic flooding is commonly considered in vehicular ad-hoc networks (VANETs) to alleviate the celebrated broadcast storm problem. Heuristics and simulations have so far proved to be an efficient way with which to design probabilistic information dissemination solutions with demonstrated effectiveness. Supplementing with mathematical analysis for both design and evaluation is expected to generalize the results, and increase the confidence in the proposed solutions. So far, this has been limited due to the difficulties associated with the underlying stochastic dependencies. In this paper, we introduce simple models of single and multiple lane roads to design effective probabilistic flooding schemes for VANETs. The proposed analytical framework offers a novel and generic tool which can cover any number of lanes, vehicle transmission range, and density. We derive difference equations whose solutions yield the probability of all vehicles receiving the emergency warning message as a function of the rebroadcast probability, the number of neighbors of each vehicle, and the dissemination distance. The models are validated using simulations, realistically representing both the traffic and networking aspects, and are used as a baseline to design two schemes for information dissemination which employ probabilistic flooding. The one attempts direct calculation of the required parameters whereas the other adaptively regulates the rebroadcast probability based on the vehicle speed. The schemes are evaluated using simulations and are found to achieve significant performance improvements compared to blind flooding with respect to the achieved reachability, end-to-end delay, and number of rebroadcasts, comparable to the performance achieved by optimal flooding, obtained via brute force.

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.

5G will require a number of Key Technological Components to meet its very ambitious goals, including Heterogeneous Networks a nd Small Cells. The Dense Deployme nt of Small Cell Base Stations (SBSs) will play a major role as they can be installed in a more targeted manner to relieve traffic in hot spot areas, increase coverage, and spectral efficiency. However, the current deployment of the SBS is static (examples include Femto, Pico, and Nano cells), normally deployed on demand around hotspots. In the scenario of unpredictable crowd movement, these static deployment of small cell can be inefficient with high CAPEX and OPEX. This paper focuses on the scenario where UE-based Virtual Small Cell Base Stations (UE-VBSs) can be dynamically selected among UEs to deal effectively with the non-stationary, non-uniform distribution of mobile traffic with respect to time and space domain. To implement this concept, we propose an efficient clustering technique (Affinity Propagation Clustering) to select the best set of UE-VBSs to supplement an overlay loaded SBS. Simulative evaluation highlights salient features of the technique, as well as its limitations with regard to scalability. Further, we discuss the modification of the algorithm according to our objec tive sc enario focusing on red ucing the message passing procedure to and from only a number of eligible UE-VBSs using the power received by a UE from the eligible UE-VBSs as a parameter. The algorithm is implemented and evaluated in MATLAB and, also validated using NS3 simulator.

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.

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.

We review harvested energy prediction schemes to be used in wireless sensor networks and explore the relative merits of landmark solutions. We propose enhancements to the well-known Profile-Energy (Pro-Energy) model, the so-called Improved Profile-Energy (IPro-Energy), and compare its performance with Accurate Solar Irradiance Prediction Model (ASIM), Pro-Energy, and Weather Conditioned Moving Average (WCMA). The performance metrics considered are the prediction accuracy and the execution time which measure the implementation complexity. In addition, the effectiveness of the considered models, when integrated in an energy management scheme, is also investigated in terms of the achieved throughput and the energy consumption. Both solar irradiance and wind power datasets are used for the evaluation study. Our results indicate that the proposed IPro-Energy scheme outperforms the other candidate models in terms of the prediction accuracy achieved by up to 78% for short term predictions and 50% for medium term prediction horizons. For long term predictions, its prediction accuracy is comparable to the Pro-Energy model but outperforms the other models by up to 64%. In addition, the IPro scheme is able to achieve the highest throughput when integrated in the developed energy management scheme. Finally, the ASIM scheme reports the smallest implementation complexity.

Nanonetworks comprise numerous wireless nodes, assembled at micro-to-nano scale. The unique manufacturing challenges and cost considerations of these networks make for minimal complexity solutions at all network layers. From a networking aspect, packet retransmissions should be kept minimal, while ensuring communication between any two nanonodes. In addition, assigning unique addresses to nanonodes is not straightforward, since it can entail a prohibitively high number of packet exchanges. Thus, efficient data routing is considered an open issue in nanonetworking. The present paper proposes a routing system which can be dynamically deployed within a nanonetwork. Static, dense topologies with numerous, identical nodes are examined. These attributes are especially important in the context of recently proposed applications of nanonetworks. The proposed scheme incurs a trivial setup overhead and requires integer processing capabilities only. Once deployed, it operates efficiently, inducing lower packet retransmission rates than related schemes.

As online eco-feedback social applications are being increasingly used around the world for motivating citizens to become more energy-aware, privacy concerns in terms of sharing personal electricity consumption data among online contacts are rising. Through Social Electricity, an online application offering personal energy management through a social and collaborative environment, we study the privacy concerns of the users in two case studies, in Cyprus and Singapore. For the Cyprus case, we present an analysis of results gathered through a large questionnaire-based survey combined with mini focus group studies. For the Singapore case, we analyze the findings collected through a students' semester exercise. This paper provides interesting insights about the overall acceptance and tolerance levels of users of eco-feedback social applications.

Gamma Deployment is a metric for evaluating the distribution of roadside units in vehicular networks in terms of two parameters: a) the inter-contact time between vehicles and the infrastructure, and, b) the share of vehicles that must respect the inter-contact time guarantees. We envision the use of the Gamma Deployment metric when the network designer intends to distribute check-points along the road network in order to collect and disseminate traffic informations through roadside units. Thus, the goal is to locate the roadside units such that ρ percent of vehicles meet roadside units in time intervals less than τ seconds. In this work, we formalize the Gamma Deployment metric by developing an Integer Linear Programming formulation (ILP). Since the ILP is not able to solve large instances, we also develop an heuristic for approximating the optimal solution. We present experiments considering a realistic mobility trace, and our results demonstrate the heuristic incurs in small deviations for small inter-contact time guarantees.

A number of probabilistic flooding schemes have been recently considered in VANETs to address problems of information dissemination in safety applications. The design approach has so far been simulative, a method which does not guarantee that the derived protocols will work when the simulation settings are violated in practice. In this paper, motivated by the need to design information dissemination protocols with verifiable properties prior to implementation, we employ mathematical models of single and multiple lane roads to investigate probabilistic flooding in VANETs using mathematical analysis. We demonstrate that the system can be described by linear difference equations the solutions of which yield the probability of all vehicles receiving the critical message as a function of the rebroadcast probability, the number of neighbors of each vehicle and the number of vehicles. We utilize the obtained solutions to derive the desired rebroadcast probabilities as a function of the transmission range, the vehicle density and the dissemination distance. The obtained results are in line with results obtained using extensive simulations and can be used as a baseline to develop information dissemination protocols with verifiable properties.

As the Internet of Things (IoT) and the Web of Things (WoT) are becoming a reality, their interconnection with mobile phone computing is increasing. Mobile phone integrated sensors offer advanced services, which when combined with Web-enabled real-world devices located near the mobile user (e.g., body area networks, radio-frequency identification tags, energy monitors, environmental sensors, etc.), have the potential of enhancing the overall user knowledge, perception and experience, encouraging more informed choices and better decisions. This paper serves as a survey of the most significant work performed in the area of mobile phone computing combined with the IoT/WoT. A selection of over 100 papers is presented, which constitute the most significant work in the field up to date, categorizing these papers into ten different domains, according to the area of application (i.e., health, sports, gaming, transportation, and agriculture), the nature of interaction (i.e., participatory sensing, eco-feedback, actuation, and control), or the communicating actors involved (i.e., things and people). Open issues and research challenges are identified, analyzed and discussed.

This work is concerned with the problem of efficient and intelligent message forwarding in wireless networks. This problem arises in many diverse scenarios within ad-hoc networks and especially networks formed during and in the aftermath of a disaster in which infrastructure-based communication systems have been damaged or completely destroyed. Within this setting, mobile devices need to support critical message exchanges in order to offer user reassurance and aid first responders' search-and-rescue operations. Notably, the dissemination of alert messages has to be done in a way that achieves sufficient dissemination while ensuring network longevity. Under the proposed explore and exploit (EnE) framework, this paper derives innovative networking heuristics that capitalizes on locally-calculated metrics (including the Local Connectivity (LC) centrality metric) to make message forwarding/replication decisions. The proposed heuristics exhibit excellent features with regards to the aforementioned performance objectives and are shown to greatly outperform current popular alternative solutions.

Wireless sensor networks (WSNs) face a number of security challenges that can compromise their operation. A typical security attack that can be launched by an adversary, in order to affect the network's communication, is the selective forwarding attack. If compromisation occurs, it is essential to recover the network to a stable state. In the context of mission-critical WSNs the challenge is not just to recover from compromisation but it is vital to restore an enhanced network operation in order to support a reliable decision-making. Sensor nodes usually address the selective forwarding attack by deploying blacklisting and rerouting. These countermeasures have been proposed in the context of omni-directional networks. This research work investigates the utilization of directional antennas in WSNs in order to increase the recovery benefits gained by the blacklisting and rerouting countermeasures in terms of reliability, survivability and responsiveness, attributes that are vital for the operation of mission-critical applications.

The high popularity of Wi-Fi technology for wireless access has led to a common problem of densely deployed access points (APs) in residential or commercial buildings, competing to use the same or overlapping frequency channels and causing a degradation to the user experience due to excessive interference. This degradation is partly caused by the restriction where each client device is allowed to be served only by one of a very limited set of APs (e.g. belonging to the same residential unit), even if it is within range of (or even has a better signal quality to) many other APs. In this paper, we propose a cooperative strategy to mitigate the interference and enhance the quality of service in dense wireless deployments, by having neighboring APs agree to take turns (e.g. in round-robin fashion) to serve each other's clients. We present and analyze a cooperative game-theoretic model of the incentives involved in such cooperation and identify the conditions under which cooperation would be beneficial for the participating APs.

In this study, we describe an effective video communication framework for the wireless transmission of H.264/AVC medical ultrasound video over mobile WiMAX networks. Medical ultrasound video is encoded using diagnostically-driven, error resilient encoding, where quantization levels are varied as a function of the diagnostic significance of each image region. We demonstrate how our proposed system allows for the transmission of high-resolution clinical video that is encoded at the clinical acquisition resolution and can then be decoded with low-delay. To validate performance, we perform OPNET simulations of mobile WiMAX Medium Access Control (MAC) and Physical (PHY) layers characteristics that include service prioritization classes, different modulation and coding schemes, fading channels conditions, and mobility. We encode the medical ultrasound videos at the 4CIF (704 × 576) resolution that can accommodate clinical acquisition that is typically performed at lower resolutions. Video quality assessment is based on both clinical (subjective) and objective evaluations.

Researchers have designed intrusion recovery protocols in Wireless Sensor Networks (WSN) with the aim of restoring compromised services and promoting a secure and reliable environment in WSNs. Currently, evaluation frameworks in WSNs have been proposed in a generic security context and do not constitute a representative assessment of intrusion recovery protocols. This paper proposes an evaluation methodology to aid the evaluation and comparison of intrusion recovery protocols in WSNs. The methodology defines the intrusion recovery protocol aspects that should be evaluated using a number of evaluation criteria and guides researchers in identifying the evaluation direction they should follow.

Urban residential areas are becoming increasingly dense with more and more home networks being deployed in close proximity. The paper considers a dense urban residential area where each house/unit has its own wireless access point (AP), deployed without any coordination with other such units. In this situation, it would be much better if neighbouring APs - i.e., APs that are physically close to each other - would form groups, where one member of the group would serve the terminals of all group members in addition to its own terminals, while the other access points of the group can be silent or even turned off, thus reducing interference and increasing overall Quality of Experience (QoE). The fact that participating units are deployed without any coordination makes the overall QoE vulnerable to the selfish behaviour of each unit. We propose a protocol where each unit operates in an equilibrium of a cooperative-neighbourhood game. We show using a game theoretic model that there exists a motivation for APs to enter and remain in cooperative neighbourhoods, in which interference is decreased due to the voluntary cooperation of the neighbours.

Wireless data broadcasting systems are typically assigned limited operational bandwidth due to their usually wide spatial coverage. This limitation raises issues of increased client waiting times, especially as the total size of the data to be disseminated increases. This problem could be partially or fully resolved by offloading part of the data to local mobile ad hoc subsystems. To this end, a novel merging of wireless data broadcasting and information hovering is proposed. The information hovering subsystem handles the least popular data items, allowing the most popular ones to be efficiently disseminated through the central wireless broadcasting. Both bandwidth-greedy and bandwidth-conserving cooperation algorithms are proposed. The validity of the proposed merged scheme is evaluated through simulation in a realistic MANET with locality of data demand. The results show considerably decreased mean waiting times in any case.

Wireless sensor networks (WSNs) have become a hot research topic in recent years and are considered to be one of the building blocks of pervasive computing. Many diverse, mission-critical applications are deployed, including military, rescue, healthcare, factory floor, and smart homes. Security is a fundamental requirement in such sensitive applications in order to ensure their reliable and stable operation. However, security is a fairly difficult task to achieve. The open nature of the wireless communication, the unrestricted deployment and limitations of WSNs and the existence of a variety of attacks threaten the security of a sensor network. Currently, research efforts have mainly focused on developing prevention and intrusion detection mechanisms in WSNs. Intrusion recovery is also an important aspect of security provisioning that is not given the same attention. Researchers have proposed intrusion recovery protocols to restore the network's operation when an attack is detected. Their designs are mostly based on simplified threat models, making the intrusion recovery countermeasures vulnerable to advanced threat models. Although the network may recover its operation after an attack is detected, it does not mean that the threat is eliminated. For example, a persistent adversary can adapt his intrusion strategy to compromise the deployed recovery countermeasure. This research work evaluates the robustness and reliability of well-known recovery countermeasures in WSNs against persistent adversaries. Evaluation results have shown that existing intrusion recovery solutions are vulnerable and can be exploited under different attack strategies in order to compromise the applied recovery countermeasures, and thus the network. The vulnerability assessment is carried out using ns-2 simulations in an IEEE 802.15.4 network and within the AODV context. Observations derived from the assessment contribute towards future directions that can drive new designs of intrusion recovery protocols in WSNs.

A significant issue in vehicular ad hoc networks is the design of an effective broadcast scheme which can facilitate the fast and reliable dissemination of emergency warning messages in the vicinity of an expected event, such as a car accident. In this work we propose a novel solution to this problem, which we refer to as Speed Adaptive Probabilistic Flooding. The scheme employs probabilistic flooding to mitigate the effects of the broadcast storm problem, typical when using blind flooding, and its unique feature is that the rebroadcast probability is regulated adaptively based on the vehicle speed to account for varying traffic densities within the transportation network. The protocol enjoys a number of benefits relative to other approaches: it is simple to implement, it does not introduce additional communication burden, as it relies on local information only and it does not rely on the existence of a positioning system which may not always be available. The scheme is evaluated on different sections of the highway system in the City of Los Angeles using an integrated platform combining the OPNET Modeler and the VISSIM simulator. Simulation results indicate that the proposed scheme fulfills its design objectives as it achieves high reachability and low latency of message delivery in a number of scenarios. Its robustness with respect to changing number of hops and transmission ranges is also demonstrated.

We propose a unifying framework for efficient encoding, transmission, and quality assessment of atherosclerotic plaque ultrasound video. The approach is based on a spatially varying encoding scheme, where video-slice quantization parameters are varied as a function of diagnostic significance. Video slices are automatically set based on a segmentation algorithm. They are then encoded using a modified version of H.264/AVC flexible macroblock ordering (FMO) technique that allows variable quality slice encoding and redundant slices (RSs) for resilience over error-prone transmission channels. We evaluate our scheme on a representative collection of ten ultrasound videos of the carotid artery for packet loss rates up to 30%. Extensive simulations incorporating three FMO encoding methods, different quantization parameters, and different packet loss scenarios are investigated. Quality assessment is based on a new clinical rating system that provides independent evaluations of the different parts of the video (subjective). We also use objective video-quality assessment metrics and estimate their correlation to the clinical quality assessment of plaque type. We find that some objective quality assessment measures computed over the plaque video slices gave very good correlations to mean opinion scores (MOSs). Here, MOSs were computed using two medical experts. Experimental results show that the proposed method achieves enhanced performance in noisy environments, while at the same time achieving significant bandwidth demands reductions, providing transmission over 3G (and beyond) wireless networks.

Many congestion control protocols have been recently proposed in order to alleviate the problems encountered by TCP in high-speed networks and wireless links. Protocols utilizing an architecture that is in the same spirit as the ABR service in ATM networks require estimates of the effective number of users utilizing each link in the network to maintain stability in the presence of delays. In this paper, we propose a novel estimation algorithm that is based on online parameter identification techniques and is shown through analysis and simulations to converge to the effective number of users utilizing each link. The algorithm does not require maintenance of per-flow states within the network or additional fields in the packet header, and it is shown to outperform previous proposals that were based on pointwise division in time. The estimation scheme is designed independently from the control functions of the protocols and is thus universal in the sense that it operates effectively in a number of congestion control protocols. It can thus be successfully used in the design of new congestion control protocols. In this paper, to illustrate its universality, we use the proposed estimation scheme to design a representative set of Internet congestion control protocols. Using simulations, we demonstrate that these protocols satisfy key design requirements. They guide the network to a stable equilibrium that is characterized by high network utilization, small queue sizes, and max-min fairness. In addition, they are scalable with respect to changing bandwidths, delays, and number of users, and they generate smooth responses that converge quickly to the desired equilibrium.

Social networking on the Web has become an integral part of our lives. Merging of computing with physical things enabled the conversion of everyday objects into information appliances. This merging allows Smart Homes to offer new automation possibilities to their residents. We propose utilizing existing social networking infrastructures and their Web-based APIs in order to integrate Smart Homes to the Web, offering social status to physical devices. We exploit the functionality and the Web 2.0 technologies provided by Facebook to transform the interaction with the Smart Home into a shared, social experience. A preliminary technical evaluation indicates that our approach is feasible and it offers acceptable performance.

Recently a great emphasis has been given on autonomous decentralized networks (ADNs) wherein constituent nodes carry out specific tasks collectively. Their dynamic and constrained nature along with the emerging need for offering quality of service (QoS) assurances drive the necessity for effective network control mechanisms. This study focuses on designing a robust and self-adaptable congestion control mechanism which aims to be simple to implement at the individual node, and involve minimal information exchange, while maximizing network lifetime and providing QoS assurances. Our approach combats congestion by mimicking the collective behavior of bird flocks having global self-* properties achieved collectively without explicitly programming them into individual nodes. The main idea is to dasiaguidepsila packets (birds) to form flocks and flow towards the sink (global attractor), whilst trying to avoid congestion regions (obstacles). Unlike the bio-swarm approach of Couzin, which is formulated on a metrical space, our approach is reformulated on to a topological space (graph of nodes), while repulsion/attraction forces manipulate the direction of motion of packets. Our approach provides sink direction discovery, congestion detection and traffic management in ADNs with emphasis on Wireless Sensor Networks (WSNs). Performance evaluations show the effectiveness of our self-adaptable mechanism in balancing the offered load and in providing graceful performance degradation under high load scenarios compared to typical conventional approaches.

As currently specified by 3GPP, MBMS services can be provided in a cell either by point-to-point (PtP) or point-to-multipoint (PtM) transmission mode, but not both at the same time. With PtP transmission mode, one dedicated channel (DCH) is established for each MBMS user within the cell. With PtM transmission mode one forward access channel (FACH) is established, covering the whole cellpsilas area and commonly shared by all the MBMS users within. In this paper we describe the existing 3GPP MBMS service provision approach, highlight its deficiencies, and propose a new approach to address them. To achieve this we introduce the ldquodual transmission mode cellsrdquo in which PtP and PtM transmissions can coexist and where FACHpsilas coverage range can be dynamically adapted (shrink or expand) through time based on the MBMS userspsila location within the cell. The performance evaluation performed, showed that our approach outperforms the existing 3GPP approach in terms of capacity, signaling and processing effort efficiency.

With MBMS, a mobile terminal (MT) that is on the move and receive an MBMS service may have to handover from a common to a dedicated channel when crossing the cellpsilas edge. In previous work, we highlighted the possible inefficiencies which might arise if the existing 3GPP handover control approach is adopted to execute these types of handovers and proposed a specific MBMS handover control approach that compensated for them. This approach, although effective in terms of capacity and QoS, was not very viable. Thus in this paper, using a different approach, we enhance previous work in order to address its deficiencies and make the whole solution practical. The performance evaluation showed that our enhanced proposed approach even with the enhancements made simplifying the whole handover procedure, still outperforms the existing 3GPP handover control approach in terms of capacity and QoS efficiency.

MBMS bearer services can be provided in each cell by either point-to-point or point-to-multipoint transmission mode but for efficiency a decision has to be made between the two approaches. Initially, the fundamental criterion used to make this decision was the number of MBMS users in a cell (UE counting). In this paper we extend our previous work, which proposed the power transmitted by the base station (BS) as the channel switching criterion (power counting). We evaluate our approach and illustrate its capability to dynamically adapt to continuously varying cell conditions by selecting the transmission mode in a more efficient way, preserving in this way the networkpsilas resources. At the same time we demonstrate the limitations of the conventional approach, in terms of radio resource efficiency. We show that by having the power used by the BS as the limiting factor we achieve optimized capacity during the transmission of MBMS bearer services in UTRAN.

Handover Control is one of the essential means to guarantee the continuity of mobile services to a user traveling in a cellular infrastructure, without interruption. In previous work we illustrated that using the current 3GPP specified handover control algorithm to provide continuity of MBMS (Multimedia Broadcast Multicast Service) services to a user crossing cell boundaries results either in capacity or QoS inefficiencies and proposed a new MEHO (Mobile Evaluated Handover) based MBMS handover control algorithm that compensated for them. This algorithm, although effective in terms of capacity and QoS, has some limitations concerning the way certain parameters vital for the efficient MBMS handover execution are estimated. In this paper, using a different approach (Network Evaluated Handover (NEHO)), we enhance previous work and propose a different method, that eliminates all of its predecessorpsilas deficiencies while achieving the same capacity and QoS efficiencies.

As currently specified by 3GPP, MBMS (multimedia broadcast multicast service) content can be provided in a cell by either point-to-point (P-t-P) or point-to-multipoint (P-t-M) transmission mode, but not both at the same time. In earlier work we highlighted the deficiencies of the current approach and proposed the concept of the ldquodual transmission mode cellrdquo, in which P-t-P (DCH) and P-t-M (FACH) transmissions can coexist and allowed to dynamically adapt through time, to address them. In this paper we further analyze the deficiencies of the current 3GPP approach and enhance our previous work to efficiently address the problem in high mobility scenarios as well. The proposed algorithm takes into consideration both the distribution and the movement of the MBMS userspsila within the cell (using the CPICH Ec/No signal strength as a reference) and dynamically decides which MBMS users should be served using FACH and which should be served using DCH. Simulation results show significant transmission power savings, considerable reduction on the aggregated signaling and processing effort introduced, while QoS requirements are still fulfilled.

It is beyond any doubt that the unpredictable nature of the today's Internet has tremendous impact on the transmission of video streams. With respect to the realtime nature of video streaming, unpredictable bandwidth, end-to-end delay and packet loss, are all problems that can affect video streaming over the Internet. The problem is worsened when we consider wireless and mobile users. In this paper we adopt Network Adaptation Techniques applied together with Content Adaptation Techniques to achieve graceful performance degradation as network load increases. We present a novel feedback mechanism and a fuzzy oriented decision algorithm which collectively provide video adaptation to network parameters. Our preliminary performance evaluations indicate that the fuzzy-based algorithm can finely sense the available bandwidth of the network path and adapt the video transmission rate accordingly, maintaining acceptable video quality.

In this paper we present MicroPulse, a novel framework for adapting the waking window of a sensing device S based on the data workload incurred by a query Q. Assuming a typical tree-based aggregation scenario, the waking window is defined as the time interval r during which S enables its transceiver in order to collect the results from its children. Minimizing the length of r enables S to conserve energy that can be used to prolong the longevity of the network and hence the quality of results. Our method is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the Critical Path Method. We show through trace- driven experimentation with a real dataset that MicroPulse can reduce the energy cost of the waking window by three orders of magnitude.

Future communication networks are envisioned to be based upon a common, flexible and scalable convergence platform, where different access networks, different terminals and different services can coexist. The new user capabilities spawn a demand forAlwaysBestConnectivity(ABC), i.e. that a user can always have the best possible connection regardless of place and time. This brings forth a new communication paradigm, which is user-centric, i.e. the user is no longer bound to only one access network but canchoosethe best available access network to satisfy a specific service request. The IP multimedia subsystem (IMS) is the technology promoted to enable this ubiquitous converged network. This paper considers the selection of access network, specifically for multicast/broadcast users and proposes a novel RAN selection scheme implemented using IMS signalling.

The transfer of information over the wireless networks is emerging as a promising business model. In addition, new applications require the transfer of video content in real time. However, the unpredictable nature of wireless and mobile networks in terms of bandwidth, end-to-end delay and packet loss has tremendous impact on the transmission of video streams. In this paper, we adopt Network Adaptation Techniques applied together with Content Adaptation Techniques to achieve graceful performance degradation when network load increases and network conditions deteriorate. We present a new feedback mechanism that provides video adaptation to network parameters, working together with a fuzzy-based decision algorithm. Our preliminary performance evaluations indicate that our algorithm can finely adapt the video stream bit rate to the available bandwidth while providing fairness as well as high and stable objective quality of service.

Handover Control in a cellular infrastructure aims to provide continuity of mobile services to a user traveling over cell boundaries. So far, Handover Control is considered only between cells supporting the service using Dedicated Resources and the handover decision making is based on a comparison between an observed signal strength value and a predetermined threshold chosen in a manner so as to maximize the overall system capacity. With the introduction of Multimedia Broadcast Multicast Service (MBMS), for radio efficiency reasons, one cell can use either Common or Dedicated resources for the distribution of the same content in a Cell. Thus, the mobile users that are on the move may have to deal with dynamic changes of network resources when crossing the cell edge, introducing new types of handovers (MBMS Handovers). Using the current Handover Algorithm when an MBMS Handover is executing will not be so efficient. For the efficient execution of these new types of handover a different approach has to be followed. This paper proposes a new Handover Algorithm which efficiently maximizes the overall system capacity when mobile MBMS users have to deal with these new types of handovers.

With the introduction of Multimedia Broadcast Multicast Service (MBMS) in 3rd Generation (3G) Networks, the Radio Network Controller (RNC) for radio efficiency reasons can use either Dedicated or Common resources to distribute the same content in a Cell. Thus the mobile users that are on the move may have to deal with dynamic changes of network resources when crossing the cell edge, introducing new types of handovers (MBMS Handovers). Executing an MBMS Handover using the current Handover Algorithm will result in inefficiencies. Therefore, for efficient execution of these new types of handover a different approach has to be followed. This paper proposes a new Handover Algorithm which efficiently maximizes the overall system capacity when mobile MBMS users have to deal with these new types of handovers.

Network resource management and control is a complex problem that requires robust, possibly intelligent, control methodologies to obtain satisfactory performance. While many Active Queue Management (AQM) mechanisms have been introduced to assist the TCP congestion control, these require careful configuration of non-intuitive control parameters, and show weaknesses to detect and control congestion under dynamic traffic changes, and a slow response to regulate queues. Furthermore, there is also a need to evaluate thoroughly the performance of such mechanisms for tandem networks containing multiple congested routers. A new AQM scheme, Fuzzy Explicit Marking (FEM) has recently been proposed to provide congestion control in TCP/IP best-effort networks using a fuzzy logic control approach. We present the control approach followed by the FEM controller, and evaluate the performance of FEM and a number of representative AQM schemes (A-RED, PI and REM) in a tandem network. An extensive simulation study over a wide range of traffic conditions shows that the FEM controller outperforms the other schemes in terms of queue fluctuations and delays, packets losses, link utilization, and speed of response to regulate queues.

In order to support mobile users, the basic Internet protocols have been extended with protocols (e.g., Mobile IPv6) for intercepting and forwarding packets to a mobile and possibly roaming node. Seamless roaming requires that users and applications do not experience loss of connectivity or any noticeable interruption in traffic. This is not only important for highly delay-sensitive traffic, but also for TCP-based traffic, as its performance is highly sensitive to packet loss and reordering. It is therefore imperative that handovers are initiated in such a way that the handover latency and packet loss is minimized. However, little is known about the performance of the proposed Mobile IPv6 approach in an actual network. In particular, it is not understood how different enhancement schemes for Mobile IPv6 influence essential performance metrics. This research paper is aimed at evaluating some of these enhancement techniques by extensive simulations to see how close we are to the ideal goal of attributing handover delay to the limitations of the physical hardware below the network layer.

It is shown that enhanced UMTS is an affordable solution for providing the required network quality and to reduce infrastructure investments in offices scenarios. System capacity results are obtained by using a system level simulator which considers traffic characterisation parameters and services usage in detail, among other. Results for the most profitable cell radius are obtained via an optimisation procedure based in economic aspects. A higher number of pico cells (with a smaller radius, around 30-32 m) can be installed in the future, when costs of deploying and maintaining the network decreases, allowing for supporting higher system capacity, and reducing prices. Our approach is based in a detailed services analysis, which represents a worst case situation relatively to the total services approach, because the later does not discriminate results for the different traffic classes. The impact of call blocking, handover failure, end-to-end delay, and delay variation are taken into account

In this paper, a novel hybrid connection admission control (CAC) scheme combining downlink transmission power and aggregate throughput in the case of dedicated and shared connection setup respectively, is presented ("DPTCAC: downlink power/throughput based CAC algorithm"). The algorithm has special applicability in the case of wireless networks with particular emphasis on 3G UMTS networks (H. Kaaramen et al., 2001) enhanced with new multicasting technologies namely in this case "multimedia broadcast-multicast service (MBMS)". The motivation for introducing this hybrid CAC approach is twofold: the need to use a representative resource metric on which to base CAC decisions and the necessity to take advantage of the particularities of the resource allocation procedure in true multicast environments with connection sharing. We first present the algorithm which is based on previously conducted work in E.S. Elayoubi and T. Chahed (2004, 2005) augment this presentation with description of the hybrid nature of our proposal. We then compare via simulations the performance of the proposed algorithm against a reference "throughput based CAC algorithm (TCAC)" (H. Holma and A. Toskala, 2001). Simulation results show a beneficial effect of DPTCAC's applicability on cell capacity without observable degradation of offered QoS

In this paper we present a soft handover algorithm for wide band CDMA based E-UMTS networks and the associated power control algorithm. The handover and power control algorithms have been developed and implemented in the framework of a system level E-UMTS simulator developed under the 1ST SEACORN project. The paper provides a background on handover design techniques and explains the handover implementation. The soft handover algorithm has been modeled using the guidelines provided in the standards and the literature for W-CDMA intra-frequency handovers. The combination of established handover techniques with enhanced UMTS is a novelty feature of this paper and provides a reference for further performance comparison

This paper presents a new system level simulator that has been developed to evaluate radio resource management (RRM) techniques in UMTS (Universal Mobile Telecommunication Systems) and enhanced-UMTS networks. The simulator includes new implementations for the user equipment, node B, radio network controller nodes and can evaluate parameters associated with UMTS or enhanced-UMTS performance, related to the introduction of RRM functions. The RRM functions implemented deal with admission control, packet scheduling, handover control, load control, and power control. The evaluation of RRM mechanisms is supported by the provision of appropriate radio propagation, traffic generation, and mobility models.

The growing demand of computer usage requires efficient ways of managing network traffic in order to avoid or at least limit the level of congestion in cases where increases in bandwidth are not desirable or possible. In this paper we developed and analyzed a generic Integrated Dynamic Congestion Control (IDCC) scheme for controlling traffic using information on the status of each queue in the network. The IDCC scheme is designed using nonlinear control theory based on a nonlinear model of the network that is generated using fluid flow considerations. The methodology used is general and independent of technology, as for example TCP/IP or ATM. We assume a differentiated-services network framework and formulate our control strategy in the same spirit as IP DiffServ for three types of services: Premium Service, Ordinary Service, and Best Effort Service. The three differentiated classes of traffic operate at each output port of a router/switch. An IDCC scheme is designed for each output port, and a simple to implement nonlinear controller, with proven performance, is designed and analyzed. Using analysis performance bounds are derived for provable controlled network behavior, as dictated by reference values of the desired or acceptable length of the associated queues. By tightly controlling each output port, the overall network performance is also expected to be tightly controlled. The IDCC methodology has been applied to an ATM network. We use OPNET simulations to demonstrate that the proposed control methodology achieves the desired behavior of the network, and possesses important attributes, as e.g., stable and robust behavior, high utilization with bounded delay and loss, together with good steady-state and transient behavior.

This paper presents a new active queue management scheme, fuzzy explicit marking (FEM), implemented within the differentiated services (Diffserv) framework to provide the congestion control using a fuzzy logic control approach. Network congestion control remains a critical and high priority issue. The rapid growth of the Internet and increased demand to use the Internet for time-sensitive voice and video applications necessitate the design and utilization of effective congestion control algorithms, especially for new architectures, such as Diffserv. As a result, a number of researchers are now looking at alternatively schemes to TCP congestion control. RED (random early detection) and its variants are one of these alternatives to provide quality of service (QoS) in TCP/IP Diffserv networks. The proposed fuzzy logic approach for congestion control allows the use of linguistic knowledge to capture the dynamics of nonlinear probability marking functions and offer effective implementation, use of multiple inputs to capture the (dynamic) state of the network more accurately, enable finer tuning for packet marking behaviors (either dropping a packet or setting its ECN - explicit congestion notification - bit) for aggravated flows, and thus provide better QoS to different types of data streams, such as TCP/FTP traffic or TCP/Web-like traffic, whilst maintaining high utilization.

The growing demand of computer usage requires efficient ways of managing network traffic in order to avoid or at least limit the level of congestion in cases where increases in bandwidth are not desirable or possible. Using non-linear control theory we developed and analysed a generic integrated dynamic congestion control (IDCC) scheme for controlling traffic using information on the status of each queue in the network. The IDCC scheme is based on a nonlinear model of the network that is generated using fluid flow considerations. The methodology used is general and independent of technology, as for example TCP/IP or ATM. We assume a differentiated-services network framework and formulate our control strategy in the same spirit as IP Diff-Serv for three types of services: premium service, ordinary service, and best effort service. The three differentiated classes of traffic operate at each output port of a router/switch. An IDCC scheme is designed for each output port, and a powerful, simple to implement controller is designed and analysed. The IDCC methodology has been applied to an ATM network. We use OPNET simulations to demonstrate that the proposed control methodology achieves the desired behaviour of the network, and possesses important attributes, such as: stable and robust behaviour, high utilisation with bounded delay and loss performance, and good steady state and transient behaviour.

We investigate the performance of a classical constrained optimisation (CCO) algorithm and a constrained optimisation genetic algorithm (GA) for solving the bandwidth allocation for virtual paths (BAVP) problem. We compare throughput, fairness and time complexity of GA-BAVP and CCO-BAVP for several node topologies. The results on maximising the throughput obtained with GA-BAVP and CCO-BAVP are in close agreement, however when considering fairness GA-BAVP outperforms CCO-BAVP, especially for more complex topologies, like the 7-node network, without abundant link capacity. Convergence of the two algorithms appears similar, with GA-BAVP outperforming CCO-BAVP in initial stages, and vice-versa for longer time scales. However as the problem complexity increases the solution time for the genetic algorithm does not increase as fast as the classical constrained optimisation algorithm. A hybrid scheme is also introduced, combining the benefits of both algorithms. It exhibited better overall convergence rate but the same solution as CCO-BAVP.

Due to the wide range of services being supported, telecommunications networks are loaded with massive quantities of information. This stimulates extra concern for network survivability. In this paper, we use graph theoretic techniques for addressing network survivability issues by transforming the original network topology onto a trellis graph, which allows the application of computationally efficient methods to find disjoint routing paths. We investigate the time complexity of the new algorithm as well as the time complexity of another algorithm on trellis transformations, presented in our previous work. The two algorithms are compared and evaluated in terms of their time complexity. Conclusions on their performance are drawn which show that the new algorithm has a better performance by a factor of n, where n is the number of nodes in the network.

Designing effective congestion control strategies for broadband networks is known to be difficult because of the variety of dynamic parameters involved such as link speeds, burstiness of the traffic, and the distances between traffic sources and switching nodes. We propose a traffic management scheme, which is insensitive to the propagation delay between the sources and switching nodes. We achieve this by combining connection admission control with a bandwidth allocation strategy. By seeking the cooperation of the available bit rate (ABR) sources (to limit their peak cell rate, PCR) at the time of admission of a variable bit rate (VBR) source to the network, the scheme eliminates the continuous congestion control. Our simulations show that the strategy is able to eliminate the ABR cell losses, achieves effective server and buffer utilization, and provides bounded delays to the VBR traffic (unlike the case without any controls).

Due to the increasing reliance of society on the timely and reliable transfer of large quantities of information (such as voice, data, and video) across high speed communication networks, it is becoming important for a network to offer survivability, or at least graceful degradation, in the event of network failure. In this paper we aim to offer a solution in the selection of the K-best disjoint paths through a network by using graph theoretic techniques. The basic approach is to map an arbitrary network graph into a trellis graph which allows the application of computationally efficient methods to find disjoint paths. Use of the knowledge of the K-best disjoint paths for improving the survivability of ATM networks at the virtual path and virtual circuit level is discussed.

We extend earlier results on the combined control problem of connection admission, flow rate, and bandwidth allocation (capacity, service-rate) in ATM based networks under nonstationary conditions to the multiple node path case. We propose a nonlinear switching strategy, and show that it is effective in controlling a mix of ABR and guaranteed traffic. We derive bounds on the mix between ABR and guaranteed traffic to ensure that control strategy is effective. The derived strategy is insensitive to propagation delay along the path, and via the setting of the values of the control design variables it can be used to influence the delivered quality of service (QoS). The performance of the proposed scheme is evaluated using analysis and simulation. Simulation results show that the proposed scheme achieves effective server and buffer utilisation (as predicted by analysis) and achieves prescribed bounded delays (for guaranteed traffic only) and zero cell loss (even for ABR traffic demands exceeding server capacity, which if not controlled would cause cell loss). Thus proposed scheme delivers guaranteed QoS to users, avoids retransmissions, and as a result increases the network utilisation and customer satisfaction.

Designing effective congestion control strategies for broadband networks is known to be difficult because of the variety of dynamic parameters involved such as link speeds, burstiness of the traffic, the distances between traffic sources and switching nodes. The uncertainties involved cause quantitative modeling of broadband networks almost impossible. Qualitative modeling techniques using the principles of fuzzy logic would lead to effective solutions. As part of our ongoing research program focusing on the development of intelligent control techniques for ATM networks, in this paper we present a regulator based on fuzzy logic control techniques for controlling congestion in broadband networks by keeping the ABR queue length around a reference value. Our simulations show that the controller is quite effective especially under network overload conditions.

We describe the fuzzy explicit fate marking (FERM) traffic flow control algorithm for a class of best effort service, known as available bit rate (ABR), proposed by the ATM Forum. FERM is an explicit rate marking scheme in which an explicit rate is calculated at the asynchronous transfer mode (ATM) switch and sent back to the ABR traffic sources encapsulated within resource management (RM) cells. The flow rate is calculated by the fuzzy congestion control (FCC) module by monitoring the average ABR queue length and its rate of change, then by using a set of linguistic rules. We use simulation to compare the steady-state and transient performance of FERM with EPRCA (a current favourite by the ATM Forum) in the presence of high priority variable bit rate (VBR) video and constant bit rate (CBR) in both a local-area network (LAN) and a wide-area network (WAN) environment. Our experiments show that FERM exhibits a robust behavior, even under extreme network loading conditions, and ensures fair share of the bandwidth for all virtual channels (VCs) regardless of the number of hops they traverse. Additionally, FERM controls congestion substantially better than EPRCA, offers faster transient response, leads to lower end-to-end delay and better network utilization.

We consider the combined control problem of connection admission, flow rate, and bandwidth allocation (capacity, service-rate) under nonstationary conditions. A fluid flow model in state variable form describes the time varying mean behaviour of available bit rate (ABR) traffic, which competes with guaranteed traffic for network resources. Using nonlinear control we derive an integrated control strategy, for the finite buffer and finite server case, that is insensitive to any propagation delay. We also derive bounds on mix between ABR and guaranteed traffic to ensure that control strategy is effective, and select control design variables which can be used to influence the delivered QoS. The performance of proposed scheme is evaluated using analysis and simulation. Simulation results show that it achieves effective server and buffer utilisation (as predicted by analysis) and by appropriate choice of control design variables achieves prescribed bounded delays (for guaranteed traffic only) and zero cell loss (even for ABR traffic demands exceeding server capacity, which if not controlled would cause losses). Hence proposed scheme delivers guaranteed QoS to user and avoids retransmissions, thus increasing network utilisation.

High-speed LANs are beginning to migrate from shared media to switch based configurations (commonly based on ATM architectures). Because of the characteristics of ATM networks and nature of LAN traffic, there is a need for effective congestion control strategies to be developed in order to maintain the network utilization and throughput at optimum levels. We describe and report the simulation results of a novel congestion control strategy based on the principles of fuzzy logic control for the management of ABR traffic in ATM LANs. We propose that fuzzy logic control is an effective scheme for designing congestion control mechanisms in ATM LANs. Our simulations show that, proposed fuzzy backward congestion notification (FBCN) method is effective in minimizing cell losses at the switch queues and prevents time consuming packet retransmissions which can dramatically degrade the network throughput.

The authors use adaptive feedback and adaptive feedforward control methodologies to avoid congestion at high server utilisation. This addresses the combined connection admission and flow control problem (generic functions for managing and controlling traffic and congestion in BISDN). Using a novel control concept, based on only two groups of traffic (controllable and uncontrollable) they formulate a problem aimed at high (unity) utilisation of resources while maintaining quality of service at prescribed levels. Bounds on operating conditions are derived, and using simulation they show that high utilisation can be achieved as suggested by the theory, together with robustness for unforeseen traffic connections and disconnections. Even with such a high efficiency and strong properties on the quality of service, the only traffic descriptor required from the user is that of the peak rate of the uncontrollable traffic. >