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This dissertation addresses certain key problems in the design of an efficient protocol stack for multihop wireless networks. We focus on the following issues: how to extend the network utility maximization (NUM) framework for resource allocation to handle both unicast and multicast traffic, and how to deal with practical issues which arise from the optimal back-pressure algorithm suggested by the NUM framework. Those practical issues consist of decentralization and complexity, as well as scalability and delay performance.
Network Optimization and Control is the ideal starting point for a mature reader with little background on the subject of congestion control to understand the basic concepts underlying network resource allocation.
We investigate a number of techniques for increasing throughput and quality of media applications over wireless networks. A typical media communication application such as video streaming imposes strict requirements on the delay and throughout of its packets, which unfortunately, cannot be guaranteed by the underlying wireless network due inherently to the multi-user interference and limited bandwidth of wireless channels. Therefore, much recent research has been focused on the joint design of network layers in order to guarantee some pre-specified Quality of Service (QoS). In this thesis, we investigate three specific settings to address the general problem of media transmission over wireless networks. In the first setting, we propose a distributed admission control algorithm in one-hop wireless network to decide whether or not a new flow should be injected into the network, in order to guarantee the QoS of the current flows. Next, a novel medium access control protocol and a scheduling packet algorithm are proposed for jointly optimizing the quality of video streaming applications. In the second setting, we extend the framework of the proposed admission control from a one-hop network to linear wireless networks, consisting of multiple nodes. In the third and final setting, we present an approach for increasing the throughput of wireless access networks by integrating network coding and beamforming techniques.
This book surveys state-of-the-art optimization modeling for design, analysis, and management of wireless networks, such as cellular and wireless local area networks (LANs), and the services they deliver. The past two decades have seen a tremendous growth in the deployment and use of wireless networks. The current-generation wireless systems can provide mobile users with high-speed data services at rates substantially higher than those of the previous generation. As a result, the demand for mobile information services with high reliability, fast response times, and ubiquitous connectivity continues to increase rapidly. The optimization of system performance has become critically important both in terms of practical utility and commercial viability, and presents a rich area for research. In the editors' previous work on traditional wired networks, we have observed that designing low cost, survivable telecommunication networks involves extremely complicated processes. Commercial products available to help with this task typically have been based on simulation and/or proprietary heuristics. As demonstrated in this book, however, mathematical programming deserves a prominent place in the designer's toolkit. Convenient modeling languages and powerful optimization solvers have greatly facilitated the implementation of mathematical programming theory into the practice of commercial network design. These points are equally relevant and applicable in today’s world of wireless network technology and design. But there are new issues as well: many wireless network design decisions, such as routing and facility/element location, must be dealt with in innovative ways that are unique and distinct from wired (fiber optic) networks. The book specifically treats the recent research and the use of modeling languages and network optimization techniques that are playing particularly important and distinctive roles in the wireless domain.
We, via a model and optimization-based approach, address three issues related to wireless networks: clock synchronization, medium access control (MAC) and scalable video streaming. In Chapter 2 we develop, study and simulate a new model-based distributed network clock synchronization protocol. In a network of clocks, a given node is taken as reference and is associated with the time evolution t. We introduce and analyze a stochastic model for clocks, in which the relative speedup of a clock with respect to the reference node, called the skew, is characterized by an exponential transformation of an Orstein-Uhlenbeck process. We study the properties of our model, namely moment and sample path properties of the stochastic processes, and calculate its Allan variance. We show how our model can be used to translate the time of a clock to another clock's units. We study the problem of synchronizing clocks in a network, which amounts to estimating the instantaneous relative skews and relative offsets, i.e., the differences in the clock readouts, by exchange of time-stamped packets between pairs of nodes in the network. Based on a stochastic model for delays, we derive a scheme for obtaining relative skew measurements in a communication link by sending two time-stamped packets from node i to node j in order to obtain a noisy measurement of their relative skew. We develop an algorithm for filtering relative skew measurements across a link (i,j) in order to estimate the logarithm of the relative skew. We study the properties of the algorithms and provide theoretical guarantees on their performance. We also develop an online, centralized, model-based, asynchronous skew estimation algorithm for optimal filtering of the time-stamps in the entire network, as well as an efficient distributed suboptimal scheme which demonstrates near-optimal performance in simulations. Furthermore, we study some implementation issues, and present a scheme for pairwise relative offset estimation given skew estimates. We use the distributed asynchronous algorithm to obtain nodal offset estimates from relative offset estimates. We combine our findings into developing a new protocol for clock synchronization, namely the Model-Based Clock Synchronization Protocol (MBCSP). We present a comparative simulation study of its performance versus the leading scheme by Solis et al. (2006); the results show that MBCSP performs better in terms of skew, offset and delay estimation. Finally, we have performed trace-driven simulation based on time-stamps obtained from Berkeley motes. Our scheme outperforms that of Solis et al. by 45%, where we used the accuracy in predicting the receipt time-stamp at the sender as the clock synchronization metric. In Chapter 3, we study random access based MAC in the framework of network utility maximization (NUM). There has been much recent interest in protocol design for wireless networks based on maximizing a network utility function. A significant advance is the observation that a decomposition of the Lagrangian suggests an approach where transmissions are scheduled to minimize back-pressure. However, a satisfactory MAC protocol that can realize such a scheduling algorithm is notably missing, and we develop one potential scheme. We present a candidate random access MAC protocol that extends an existing algorithm by Gupta and Stolyar (2006) in calculating the access probabilities. We also consider the online adaptation of access probabilities using local information about queue lengths and active links. We provide OPNET simulation results to compare the performance of our scheme with the leading schemes. We estimate the capacity region of our scheme by simulation for various topologies and multiple flows. Our simulation studies indicate that our extension in conjunction with an implementation of back-pressure significantly outperforms the slotted-time algorithm of Gupta and Stolyar (2006). In Chapter 4, we present performance bounds for random access based MAC using carrier-sense multiple access (CSMA). In recent work, it was shown that a distributed CSMA-based MAC protocol is throughput-optimal which, in turn, implies that the class of controlled distributed random access MAC protocols can support the entire capacity region. It is challenging to study the performance of such schemes in terms of mean delays and compare it with some known results on the performance of centralized scheduling. We modify the model of Jiang and Walrand (2008) to obtain Markov chain models that incorporate the queue lengths as well as the information about the independent set, for single-hop networks. We show that the delay of the new models yields an upper bound on the delay of the original models. We derive upper and lower bounds on the mean total delay at the steady-state, and show that these bounds coincide with those for max-weight scheduling. Finally, we develop a method of deriving upper and lower bounds for random-access schemes by using linear programs (LPs). We present an optimization program for minimizing the upper bounds. In Chapter 5, we consider multihomed scalable video streaming systems where each video is concurrently transmitted over several access networks to a client. The problem is to determine which video packets of a video stream to transmit, and associate each video packet with an access network, so that the video quality at the client is maximized under measured network conditions. We present a network model and a video distortion model to capture the network conditions and video distortion characteristics, respectively. We develop a mathematical formulation to find the streaming strategy for maximizing the average video quality at the client. While the formulation can be optimally solved using exhaustive search or dynamic programming, doing so takes a prohibitively long time, and is not practical for real-time video streaming servers. In order to efficiently solve the problem in real time, we propose several suboptimal convex problems along with two heuristic algorithms. We conduct extensive trace-driven simulations to evaluate the algorithms using real network conditions and actual scalable video streams. We compare our algorithms against the rate control algorithms defined in the Datagram Congestion Control Protocol (DCCP) standard. The simulation results show that our algorithms significantly outperform current systems while being TCP-friendly. For example, compared to DCCP, our algorithms achieve at least 10 dB quality improvement and result in up to 83% packet delivery delay reduction. Finally, we study the trade-off between efficiency and optimality: One of the heuristic algorithms runs faster and is suitable for large-scale streaming systems, while the other one achieves better video quality and is more appropriate for smaller streaming servers. The convex programming approach demonstrates a good trade-off between running time and performance.
This book provides a systematic treatment of the theoretical foundation and algorithmic tools necessary in the design of energy-efficient algorithms and protocols in wireless body sensor networks (WBSNs). These problems addressed in the book are of both fundamental and practical importance. Specifically, the book delivers a comprehensive treatment on the following problems ranging from theoretical modeling and analysis, to practical algorithm design and optimization: energy-efficient clustering-based leader election algorithms in WBSNs; MAC protocol for duty-cycling WBSNs with concurrent traffic; multi-channel broadcast algorithms in duty-cycling WBSNs; and energy-efficient sleep scheduling algorithms in WBSNs. Target readers of the book are researchers and advanced-level engineering students interested in acquiring in-depth knowledge on the topic and on WBSNs and their applications, both from theoretical and engineering perspective.
Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networking Mobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking. This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process—allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field. Evolutionary Algorithms for Mobile Ad Hoc Networks: Instructs on how to identify, model, and optimize solutions to problems that arise in daily research Presents complete and up-to-date surveys on topics like network and mobility simulators Provides sample problems along with solutions/descriptions used to solve each, with performance comparisons Covers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and more Evolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.
This book gives a comprehensive presentation of cutting-edge research in communication networks with a combinatorial optimization component. The objective of the book is to advance and promote the theory and applications of combinatorial optimization in communication networks. Each chapter is written by an expert dealing with theoretical, computational, or applied aspects of combinatorial optimization.
This book provides an essential overview of IoT, energy-efficient topology control protocols, motivation, and challenges for topology control for Wireless Sensor Networks, and the scope of the research in the domain of IoT. Further, it discusses the different design issues of topology control and energy models for IoT applications, different types of simulators with their advantages and disadvantages. It also discusses extensive simulation results and comparative analysis for various algorithms. The key point of this book is to present a solution to minimize energy and extend the lifetime of IoT networks using optimization methods to improve the performance. Features: Describes various facets necessary for energy optimization in IoT domain. Covers all aspects to achieve energy optimization using latest technologies and algorithms, in wireless sensor networks. Presents various IoT and Topology Control Methods and protocols, various network models, and model simulation using MATLAB®. Reviews methods and results of optimization with Simulation Hardware architecture leading to prolonged life of IoT networks. First time introduces bio-inspired algorithms in the IoT domain for performance optimization This book aims at Graduate Students, Researchers in Information Technology, Computer Science and Engineering, Electronics and Communication Engineering.
Data networking now plays a major role in everyday life and new applications continue to appear at a blinding pace. Yet we still do not have a sound foundation for designing, evaluating and managing these networks. This book covers topics at the intersection of algorithms and networking. It builds a complete picture of the current state of research on Next Generation Networks and the challenges for the years ahead. Particular focus is given to evolving research initiatives and the architecture they propose and implications for networking. Topics: Network design and provisioning, hardware issues, layer-3 algorithms and MPLS, BGP and Inter AS routing, packet processing for routing, security and network management, load balancing, oblivious routing and stochastic algorithms, network coding for multicast, overlay routing for P2P networking and content delivery. This timely volume will be of interest to a broad readership from graduate students to researchers looking to survey recent research its open questions.