Search

Device-to-device cooperation has emerged as a prominent solution to a wide range of challenges in large-scale wireless networks. However, the ad hoc nature of cooperative networks and their proneness to failure are a major obstacle towards their real world deployment and wide adoption. In this work, we focus on failure recovery and scalability in wireless content distribution networks with device-to-device cooperation, where a number of mobile devices in a given geographical area are interested in downloading a common content from an application service provider. We present low complexity effective algorithms based on clustering and tree construction methods in order to address three different types of dynamic node behavior, namely new devices joining the network, existing devices leaving the network, and existing devices moving locally within the network. Moreover, we propose a constrained version of the minimum spanning tree algorithm with bounds on the height of the tree and the maximum degree per node, in order to capture practical operational constraints for device-to-device cooperation in wireless networks. We present results for various network scenarios using simulations and experimental test bed to demonstrate the effectiveness of the proposed algorithms in terms of performance efficiency, computational complexity, and practical implementation feasibility.

Heterogeneous networks are expected to play a major role towards meeting the exploding traffic demand over cellular systems. Particularly, existing WiFi hotspots will be dynamically utilized to offload the traffic of cellular mobile subscribers. This will be further facilitated by forthcoming advances in mobile device capabilities that will include the ability to operate multiple wireless interfaces simultaneously. To this end, we focus in this work on cellular/WiFi heterogeneous networks with traffic splitting where a mobile device can utilize existing cellular and WiFi links simultaneously to achieve various performance gains. We propose a multi-objective approach for traffic splitting that captures the tradeoffs between throughput maximization on one hand and battery energy minimization on the other hand. We evaluate the proposed approach using parameters determined via experimental measurements using Samsung Galaxy SIII mobile devices. Results are presented for various scenarios in order to quantify and analyze the throughput-energy tradeoffs of traffic splitting in cellular/WiFi heterogeneous networks

Smartphones are evolving at a fast rate in terms of their computational, storage, and communications capabilities. A high-end smartphone is equipped with multiple wireless interfaces with varying bit rates, energy consumption requirements, and coverage ranges. The joint utilization of the existing wireless interfaces facilitates the development of advanced techniques to boost the performance of wireless networks and enhance the experience of mobile users. Among these techniques is device-to-device cooperation where a smartphone receives content from a base station on a given wireless interface and distributes it to other devices in its vicinity via another wireless interface. Another technique is traffic offloading in heterogeneous network scenarios where a smartphone downloads content using multiple wireless interfaces. In this paper, we study the readiness of high-end smartphones to utilize multiple wireless interfaces simultaneously focusing on capabilities and challenges. We adopt an experimental approach using a mobile cooperative video distribution testbed to obtain and evaluate performance results with focus on energy consumption. We consider various scenarios involving a combination of wireless technologies that include Bluetooth, WiFi, WiFi-Direct, and 3G.

The planning procedure of 802.11 WLAN networks is specific to each type of venue. In the case of large venues with high number and dense Wi-Fi devices, the network planning requires a deep investigation on: available channels, number of devices to associate, throughput per channels, etc. In addition, the WLAN planning of dense Wi-Fi devices becomes more complicated when adding collaboration between devices. The collaboration between devices is achieved by forwarding and sharing data through neighboring devices, named relays. In this paper, we provide guidelines for WLAN planning in high-dense collaborative environments. In addition, we study the network performance gains when content is distributed in cooperative manner through both unicast and multicast mode. Results show that using cooperative content distribution in dense environments leads to notable gain in network performance.

IP network planning based on a given traffic demand becomes obsolete as soon as the actual traffic slightly deviates from the given values. It is highly probable that this be the case in IP networks with no deployed resource control mechanisms. Complex and comprehensive resource control mechanisms are still a matter of research; while the most practical and common scenario is to have control units at the ingress of the IP network as pertained by the differentiated services architecture (DiffServ). Based on this practical model, we study the distribution of traffic demand inside the network and introduce the concept of a capacity margin, which is added to the network links in order to account for a certain level of traffic demand variability. Moreover, we analytically calculate the capacity margin and investigate the tradeoff provided between the degree of network robustness and the consequent additional costs in terms of network resources. Finally, we show how such statistical consideration of traffic variability can offer high degrees of network robustness with rather low costs.

In a classical mobile video streaming architecture, the server is responsible for processing each request from the mobile clients even if those requests are for the same content in the same geographical area. This tends to be resource exhaustive in terms of complexity, radio resources, and energy consumption especially when delivering high bit rate multimedia content. In this paper, we exploit cooperation between network technologies to reduce the load placed on a given multimedia server and reduce the overall energy drain of mobile devices. We consider a set of mobile devices that wish to receive a common video content from a designated video server. The mobile devices organize themselves into multiple Bluetooth piconets. The master in each piconet receives an H.264 encoded video content from the server via an IEEE 802.11 WLAN access point and relays it to its slave mobile devices using standard Bluetooth connections. A prototypical implementation of the proposed model in an experimental testbed is used to perform energy and video quality measurements in real conditions. Results demonstrate notable energy consumption gains while maintaining video quality in various scenarios.

We present a scalable mobile multimedia streaming system with device-to-device cooperation that enables common content distribution in dense wireless networking environments. This is particularly applicable to use cases such as delivering real-time multimedia content to fans watching a soccer game in a stadium or to participants attending a major conference in a large auditorium. The key novel characteristics of our system include seamless neighbor discovery and link quality estimation, intelligent clustering and channel allocation algorithms based on constrained minimum spanning trees, robustness against device mobility, and device centric operation with no changes to existing wireless systems. We demonstrate the functionality of the proposed system on Android devices using heterogeneous networks (cellular/WiFi/WiFi-Direct) and show the formation of multiple clusters to allow for scalable operation. The gained insights will help bridge the gap between theoretical and simulation based research conducted in this area and practical operation taking into account the capabilities and limitations of existing wireless technologies and smartphones/tablets.

In our previous work, we proposed and evaluated an end-to-end scheduling approach for allocating resources to mobile users with end-to-end delay requirements. The novelty of the proposed approach is that it ensures an end-to-end utility in terms of delay and frame success rate by simultaneously considering both the time varying channel conditions in the uplink and the downlink directions. In this work, we extend the end-to-end scheduling approach by designing and evaluating a joint scheduling and BS assignment algorithm in order to further improve the system performance. Moreover, we extend the system model to include heterogeneous services with varying quality parameters. Results show that the performance gains, in terms of higher average number of active connections and lower packet drop ratio, increase notably with joint BS assignment depending on the level of distribution of users in the network.

Node failures in distributed storage systems are becoming a critical issue, and many erasure codes are designed to handle such failures. The purpose of this paper is to evaluate fractional repetition (FR) codes, a class of regenerating codes for distributed storage systems, as a practical solution. FR codes consist of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. We model the problem as an integer linear programming problem that uses modified versions of the fractional repetition code by allowing different block sizes, and minimizes the recovery cost of all single node failure scenarios. The contribution of this work is three fold: We generate an optimized block distribution schema that minimizes the total system repair cost in a data center and we present a full recovery plan for the system. In addition, we account for new-comer blocks and allocate them to nodes with minimal computations and without changing the original optimal schema. This makes our work practical to apply. Hence, a practical solution for node failures is presented by using a self-designed genetic algorithm that searches within the feasible solution space. We show that our results are close to optimal.

Bluetooth wireless technology is being installed in almost any electronic or information device for ad-hoc connectivity among them. Up to eight Bluetooth devices can form a network called a piconet. Interconnecting multiple piconets through gateway devices forms a scatternet. In the Bluetooth specifications, no scatternet topology has been specified. This paper proposes a scatternet formation topology that, unlike the existing literature, considers the non-uniform distribution of Bluetooth devices. Our proposed approach dictates a ring topology formed in the dense area and extended by trees to the other areas. The proposed approach is denoted as BlueHRT: Hybrid Ring Tree Scatternet Formation in Bluetooth Networks. Results are presented to highlight the performance gains of the proposed approach.

As a basis for planning integrated QoS-enabled IP networks, proper evaluation of link capacities is needed to provide the desired level of quality for all supported classes in the network. As traffic characteristics and requirements of these classes are quite different, various dimensioning schemes are required, each estimating the share of capacity needed for its corresponding class. In S. Sharafeddine et al. (July 2003), a dimensioning method has been proposed to provide almost guaranteed quality of service for real-time traffic classes. While this method is applied for dimensioning single links, we propose in this work an appropriate extension that enables end-to-end capacity allocation. Moreover, we realize the given capacity planning problem in a dimensioning tool that supports different traffic classes belonging to the two broad categories, namely stream and elastic traffic. For this purpose, per-hop mapping of end-to-end QoS constraints is handled and a generic layered architecture is proposed and implemented.

Content distribution applications such as video streaming and file sharing are posing strict requirements on the development and enhancement of architectures and protocols for wireless networks. In this work, we address the problem of collaborative content distribution where destination content-requesting nodes collaborate by sharing over mobile-to-mobile links data blocks received from a source node, e.g., a wireless access point. We propose a dynamic collaborative content distribution protocol that is capable of minimizing the end-to-end distribution delays in the network. Moreover, we present simulation results for three network scenarios to analyze the behavior of the proposed protocol.

Multimedia applications are migrating to IP networks imposing high challenges on network planners. Challenges arise due to the stringent quality of service (QoS) requirements of multimedia applications that cannot be met over enterprise IP networks unless advanced techniques and strategies are applied. Example techniques are traffic differentiation, capacity evaluation and reservation, and call admission control. In this work, we assume practical call admission control (CAC) schemes and study by simulations the distribution of traffic inside the network. We show how capacity needs of traffic are affected when various CAC schemes are employed. Finally, we identify a procedure to evaluate the link capacity share for realtime traffic and study the resulting tradeoff between capacity needs and QoS parameters such as packet loss and blocking probability.

Wireless cellular networks are required to meet the stringent QoS requirements of emerging data services. To efficiently utilize the available radio resources, we propose a new resource allocation algorithm for services that require end-to-end guarantees. Unlike existing literature that mainly focuses on downlink only or uplink only scheduling algorithms, the proposed algorithm aims at ensuring an end-to-end utility value reflecting end-to-end QoS in terms of delay and channel quality. By jointly considering the time varying channel conditions in both uplink and downlink directions, the proposed end-to-end scheduling algorithm achieves an increased number of active connections and a lower packet drop in comparison to other schemes. These gains are achieved with a tradeoff cost in terms of complexity and signaling overhead. For overhead reduction, we propose an implementation over clusters within the network.

Content distribution applications such as video streaming, file sharing, and network gaming are posing strict requirements on the development and enhancement of communications technologies, architectures, and protocols. Collaboration is one of the central techniques for designing enhanced communication networks. In this work, we address the problem of collaborative content distribution where destination nodes collaborate by sharing, over peer-to-peer connections or mobile-to-mobile links, data blocks received from a source node. We calculate the total number of possible distribution trees as a function of the number of data blocks and destination nodes for a two-level hierarchy, and generalize results to a multilevel hierarchy. Moreover, we develop a content distribution cost model and discuss special case content distribution scenarios.

Third generation CDMA networks strive to deliver high speed data services through a shared radio channel with scarce resources. To efficiently utilize the available radio resources, we propose a new scheduling algorithm based on techniques from micro-economics. Unlike existing literature that mainly focuses on maximizing total system and/or individual user utility, this new algorithm aims at ensuring QoS guarantees from end to end for all active connections. Moreover, it considers the time varying channel conditions in both uplink and downlink directions jointly rather than each direction separately. Simulation results show that the proposed algorithm allows several users to simultaneously transmit while providing end-to-end QoS guarantees in terms of frame success rate and end-to-end delay.

One key enhancement in recent 3GPP cellular standard releases is WiFi/cellular network inter-operation and integration with protocols and techniques that can optimize target performance metrics. 3GPP specifications focus on network- centric solutions that require the involvement of the cellular operator in the WiFi/cellular connection and mobility management procedures. Even though this provides notable gains due to the centralized control, its implementation requires network upgrades and is relatively complex which limits the possibility of quick market penetration. In this work, we present a practical and effective device-centric WiFi/cellular link aggregation mechanism that can boost the download bit rate and minimize the download delay. The proposed mechanism is self-adaptive and achieves optimized aggregated download bit rate without the need for link quality estimation information, changes to the WiFi or cellular standards, or proxy server configuration. Moreover, it can be customized to support different service classes as shown for file downloading and video streaming applications. We do extensive testing using an experimental implementation over Android smartphones in order to demonstrate the practical feasibility of the proposed mechanism and to quantify its performance gains under different operational conditions.

Ultra dense networks and device-to-device communications are expected to play a major role in 5G networks to meet tremendous traffic requirements. In our work, we address traffic offloading in dense device-to-device cooperative heterogeneous networks with focus on use cases where a very large number of users request simultaneously common streaming content from a remote server with quality of service guarantees. We formulate an optimization problem to maximize the number of users served and reduce the number of access points deployed while satisfying a set of system constraints. The solution determines the best strategy for downloading the content either over long range connectivity from the access points or short range connectivity from peer mobile devices. Results are presented for various scenarios in a stadium setting to demonstrate the significant gains of optimized traffic offloading in ultra dense wireless networks.

A single bit transmission over the wireless card can consume 1000 times more energy as compared to a 32-bit CPU computation. This fact is very critical for devices operating on limited battery such as mobile devices. In this work, we propose a new approach that utilizes a lightweight compression scheme for the to-be-transmitted data in an adaptive manner. In our approach, the signal strength is being monitored during the transmission process and blocks of data are compressed on-the- fly only when energy gain is promised. This paper explains the proposed adaptive approach and presents energy measurement results that show significant gains in energy as compared to the always-compress or no-compress schemes.

Transport of compressed video is expected to pervade computer networks in the near future. Video is commonly encoded in variable bit rate traffic to improve video quality and reduce encoding delays and yet to make efficient use of the available capacity using statistical multiplexing. Variable bit rate coded video imposes a real challenge to network planners who aim to evaluate its necessary capacity share. In this paper, we present a dimensioning model tailored especially for variable bit rate video transmission over IP networks taking the network delay into account unlike existing dimensioning models. We investigate this new model in terms of different system parameters.

Providing hard quality of service guarantees for Voice over IP traffic in multi-service IP networks is quite costly in terms of network resources. However, if one is willing to slightly soften the guarantees and to accept a small probability of service degradation, the amount of capacity necessary for voice traffic can be greatly reduced. In this paper, we investigate the tradeoff between quality of service and the required bandwidth for voice traffic in IP networks taking into account different scheduling schemes. We propose a dimensioning strategy, which allows the worst-case packet delay to exceed a desired threshold with a certain probability. Based on simulations, it can be demonstrated that bandwidth is reduced while the quality of service is assured in most cases.

With the current exponential growth in traffic and service demands, device-to-device (D2D) cooperation is identified as a major mechanism to enable 5G networks to effectively and efficiently augment network resources. The effectiveness of D2D cooperation depends on a wide range of decision making processes that include cluster formation, resource allocation, in addition to connection and mobility management. Irrespective of the D2D cooperation scenario whether in sensor, ad hoc, or cellular networks, the literature normally assumes that devices selected as relays or data sources are reliable; this means that they will maintain the connection till the communication session ends. Yet, this assumption is challenged in practice since devices’ batteries can be depleted (e.g., sensors in an IoT network) and devices can move leading to connection termination (e.g., mobile users in a WiFi network or cars in a vehicular ad hoc network). To this end, we address the problem of reliable D2D cooperation in wireless networks by proposing a novel approach that is proactive by utilizing reliability metrics in the decision making process, and scalable by having low implementation complexity suitable for dense networks. These differentiating factors are shown to enhance the overall network reliability compared to standard techniques and to facilitate dynamic operation which is essential for practical implementation. Performance is evaluated using extensive simulations in addition to test bed experimental demonstration in order to quantify gains and extract insights on a range of existing design tradeoffs.

In this paper, we address the problem of capacity assignment for latency-sensitive traffic in multi-service IP networks. The capacity assignment (CA) problem is formulated as an optimization problem with nonlinear constraints, where the total link capacity shares allocated to the given service are minimized subject to performance constraints in terms of endto-end delay requirements. We introduce a new extension to traditional CA problems by setting a statistical bound on the maximum end-to-end delay experienced by all packets associated with the given latency-sensitive service. For a sample IP network scenario with VoIP traffic, we show that only 3% of additional capacity as compared to the classical approach is required to keep the probability of exceeding the maximum end-to-end delay threshold below 0.1%

Due to the exploding traffic demands with the ubiquitous anticipated spread of 5G and Internet of Things, research has been active to devise mechanisms for meeting these demands while maintaining high quality user experience. In support of this direction, 3GPP is working towards cellular/WiFi interworking in heterogeneous networks to boost throughput, capacity, coverage and quality of experience. However, the continuous use of multiple wireless interfaces will increase the system performance but at the expense of more energy. As a result, there is a need for a dynamic use of multiple interfaces to provide a balance between energy consumption, throughput and user experience. Previous work in this field has considered improving throughput and reducing energy consumption, but did not consider simultaneously quality of experience as perceived by the end user. In this work, we aim at devising real-time traffic splitting strategies between WiFi and cellular networks to maximize user experience, reduce delay, and balance the needed energy consumption. We develop solutions for cellular/WiFi network resource management using Lyapunov drift-plus-penalty optimization approach. We evaluate the proposed approach using parameters determined via experimental measurements from mobile devices, and using our own test bed implementation to provide an evaluation under realistic operation conditions. Results show the performance effectiveness of the proposed traffic splitting approach in terms of throughput, delay, queue stability, energy consumption and quality of user experience by monitoring the frequency and lengths of video stalls.

Device-to-device (D2D) offloading has been shown to be a highly effective technique to enhance the performance of wireless networks. Yet, for any two mobile users to share data efficiently and reliably via D2D links, they should be in close proximity for long enough period of time, share similar content interests, and have some level of incentive and trust to cooperate. In this work, we focus on the practical implementation aspects of D2D data sharing taking into account realistic operational conditions. To this end, we design and conduct an experimental study to collect location and neighbor discovery data from 38 mobile users in a university campus over several weeks using our own customized crowdsourcing Android mobile application. The collected data is then processed and utilized to empirically model mobility-related parameters that include contact frequency, contact duration, and inter-contact duration. The participating users did also fill a user interest survey in order to correlate mobility and connectivity patterns with content interests and social network relations. The obtained insights are then used to develop a practical implementation framework for designing effective D2D data sharing strategies. To test the proposed ideas under realistic operational constraints, we design and implement a social-aware D2D data sharing Android mobile application and demonstrate its functionality and effectiveness using an example case study scenario

Traditional error recovery schemes such as automatic repeat request (ARQ) and incremental redundancy rely on immediate retransmissions to deal with bit errors or packet losses. This immediate retransmission approach leads to increased energy consumption and performance degradation for multimedia communications over wireless networks especially when the probability of data error is high. Moreover, retransmissions negatively impact the performance of other mobile nodes due to the nature of resource sharing in wireless networks. In this work, an energy-aware retransmission scheme is designed, implemented, and evaluated. The proposed scheme adapts packet retransmissions based on both the received signal level at the mobile nodes and the data reception success rate. Performance results using ns-2 simulations demonstrate notable reduction in energy consumption. Results also show that the proposed scheme outperforms the default 802.11b medium access control (MAC) protocol in terms of packet delay which is an important metric for multimedia applications.

As voice services impose stringent quality of service (QoS) guarantees to perform well over IP networks, large network resources should be allocated to their traffic class. It gets unaffordable when hard guarantees are required as in deterministic-based mechanisms such as the guaranteed services model of the integrated services (IntServ) architecture. However, the amount of network resources could be drastically decreased if only a small number of all voice connections are allowed to be negatively affected. In this work, a new capacity allocation method based on the maximum waiting time model is explored. It is established from the following concept: by providing statistical quality guarantees to those packets that experience the maximum waiting time among all packets of the active voice connections, all other packets are implicitly protected from excess delay and, thus, from service degradation. This method is investigated and mathematically analyzed for the voice service class in converged IP networks.

In this paper, a channel aware resource reservation protocol for content distribution in an OFDMA wireless network with mobile-to-mobile cooperation is presented. The proposed approach consists of a reservation phase and a transmission phase. The proposed protocol uses channel information in order to avoid unnecessary reservations and thus reduce collisions. The purpose of the proposed protocol is to overcome several practical limitations of the optimal content distribution solution with energy minimization. Simulation results show that the proposed protocol can lead to efficient content distribution between mobile terminals, at the expense of a moderate increase in energy consumption, compared to the optimal solution.

Energy efficient content distribution with mobileto-mobile cooperation is considered. The distribution method is based on long range transmission from a base station and on short range cooperation between mobile terminals. Long range communication is assumed over an LTE network whereas Bluetooth is considered on the short range. A low complexity energy-efficient content distribution approach is presented and compared to the optimal solution. Results show that the proposed approach leads to more fairness than the optimal solution, at the expense of a slight performance degradation in terms of energy savings. However, significant energy savings are obtained compared to the scenario without mobile-to-mobile cooperation. Thus, the use of Bluetooth in cooperative short range communications can lead to increased energy efficiency for mobile terminals.

Wireless broadband technologies and services are witnessing exponential growth to meet the demands of mobile users. State-of-the-art wireless networks are evolving with enhancements spanning all protocol layers and all network components from radio access to core network nodes. This has been coupled with a tremendous transformation of end user mobile devices towards multi-purpose smartphones and tablets with multi-core processing power, extendable memory storage, large battery capacity, and support for a wide range of wireless connectivity options. A standard smartphone currently can support short range Bluetooth and WiFi-Direct connectivity, local area WiFi connectivity, and long range 2G/3G/4G mobile connectivity. This naturally provides opportunities for data aggregation utilizing multiple wireless interfaces simultaneously to enhance device and network performance. In this work, we present the design, implementation, and testing of optimized device-centric data aggregation mechanisms for both file downloading and video streaming applications. The main novelty of the proposed mechanisms is their device-centric design, which makes them practical and feasible without any changes to wireless standards; moreover, they are scalable to support any number of wireless interfaces whereas previous related work has dealt with devices having two interfaces only. To demonstrate the effectiveness of the proposed mechanisms in terms of performance gains and practical feasibility, we develop an experimental testbed using Android devices and perform extensive testing for several network scenarios.

In just few years, the Field of data communication and computer networking has matured considerably in terms of theory and application. Almost every university is offering one or more courses in this field but unfortunately very few universities have a laboratory for such courses. Our aim in this thesis is to provide the student with a practical environment to verify the fundamental concepts and theories learned in the classroom.--This thesis is for a laboratory course that supplements a lecture course on the subject. It includes ten experiments with each experiment adding to the student's knowledge in networking and in programming. We have selected a varied set of topics that corresponds to the issues addressed at the different layers of the OSI model network architecture. The knowledge acquired throughout the course of development of the experiments advances smoothly in terms of theoretical and programming skills.

Data communications and computer networking (DCCN) has established itself as an essential part of most computer science and engineering curricula, usually in the form of courses and/or laboratories. For reliable training in this area, this study presents a series of 10 experiments that serve as a complete laboratory course in DCCN. The prominent benefit of this laboratory set is that it uses available UNIX workstations where networking is simulated using software; this overcomes the obstacle of unavailable or expensive hardware and communication resources. The experiments presented here cover all layers, except the physical layer, of the Open Systems Interconnection (OSI) model. In addition to introducing the student to this wide‐ranging subject matter, the laboratory set enhances his/her programming skills. This is accomplished by introducing the UNIX programming environment and using it to carry out the experiments, starting with editing and compiling simple programs, and ending with implementing advanced client‐server applications. © 2004 Wiley Periodicals, Inc. Comput Appl Eng Educ 12: 84–97, 2004; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20002

In this paper, we address the problem of capacity assignment (CA) for latency-sensitive traffic in multi-service IP networks. The CA problem is formulated as an optimization problem with nonlinear constraints, where the total link capacity shares allocated to the given service are minimized subject to performance constraints in terms of end-to-end delay requirements. We introduce a new extension to traditional CA problems by setting a statistical bound on the maximum end-to-end delay experienced by all packets associated with the given latency-sensitive service. For a sample IP network scenario with VoIP traffic, we show that a relatively slight increase in capacity as compared with the classical approach is required to keep the probability of exceeding the maximum end-to-end network delay threshold below 0.1%.

Quantifying and modeling energy consumption in mobile devices are essential for developing energy-aware protocols and energy reduction techniques. In this work, we address the energy requirements for secure Web browsing sessions over handheld mobile devices. The contributions of this work are twofold. On one hand, we present a detailed study based on experimental measurements to quantify the energy consumed by the mobile device during secure Web browsing sessions. This includes the energy consumed due to data transmission/reception, encryption/decryption, hashing in addition to browser processing. On the other hand, we derive an empirical energy consumption model for secure Web browsing as a function of various protocol and device parameters. The developed model can be utilized to identify the various components that affect energy consumption during secure Web browsing sessions, to implement application-layer energy models in network simulation tools, and to develop adaptive energy-aware Web browsing protocols. The effectiveness of the developed model is demonstrated via experimental testing on several secure websites.

Cooperation between mobile terminals (MTs) with the objective of energy minimization is studied. The purpose is to distribute a content of common interest to collaborating MTs while ensuring a reduced energy consumption. To reach this goal, the content is sent to selected MTs on a long-range link. Then, it is forwarded to other MTs on short-range mobile-to-mobile links. The problem is formulated as an optimization problem, and the optimal solution is shown to consist of sending the content to a single MT on the long-range link and of having that MT distribute it on the short-range links. This leads to an unfair energy consumption for the selected MT. Thus, to ensure fairness in energy consumption, a low complexity utility minimization algorithm is proposed. Using the appropriate utilities, the algorithm can be used to implement the optimal greedy energy minimization solution or to ensure different degrees of fairness in energy consumption. Practical constraints concerning the centralised and distributed implementations of the proposed algorithm are also discussed. Simulation results show that significant energy savings can be achieved with the proposed approach compared with the non-collaborative case. In addition, a tradeoff between fairness and energy savings is achieved depending on the utility selected

Network planning for realtime services in traditional systems is normally performed based on a fixed traffic demand. Realtime services such as voice and video are currently being widely deployed over packet-based IP networks. Due to the lack of resource control mechanisms in IP networks, the actual traffic during network operation may easily deviate from the given mean traffic matrix values. As realtime services impose stringent quality of service (QoS) constraints, any traffic deviation inside the network might lead to severe quality degradation if any of the links provides insufficient service rate for the available traffic at any time. In this work, we highlight the significance of this problem and propose an effective approach to provide a highly robust network against traffic deviation. By means of both analytical and simulation studies, we study the distribution of realtime connections over an enterprise IP network and show how capacity needs of realtime traffic are affected when various resource control mechanisms are employed. In addition, we study the resulting tradeoff between capacity needs and traffic QoS parameters including packet loss and blocking probability.