Stable Wireless Network Control Under Service Constraints

We consider the design of wireless queueing network control policies with particular focus on combining stability with additional application-dependent requirements. Thereby, we consequently pursue a cost function based approach that provides the flexibility to incorporate constraints and requirements of particular services or applications. As typical examples of such requirements, we consider the reduction of buffer underflows in case of streaming traffic, and energy efficiency in networks of battery powered nodes. Compared to the classical throughput optimal control problem, such requirements significantly complicate the control problem. We provide easily verifyable theoretical conditions for stability, and, additionally, compare various candidate cost functions applied to wireless networks with streaming media traffic. Moreover, we demonstrate how the framework can be applied to the problem of energy efficient routing, and we demonstrate the aplication of our framework in cross-layer control problems for wireless multihop networks, using an advanced power control scheme for interference mitigation, based on successive convex approximation. In all scenarios, the performance of our control framework is evaluated using extensive numerical simulations.Comment: Accepted for publication in IEEE Transactions on Control of Network Systems. arXiv admin note: text overlap with arXiv:1208.297

Optimal Distributed Scheduling in Wireless Networks under the SINR interference model

Radio resource sharing mechanisms are key to ensuring good performance in wireless networks. In their seminal paper \cite{tassiulas1}, Tassiulas and Ephremides introduced the Maximum Weighted Scheduling algorithm, and proved its throughput-optimality. Since then, there have been extensive research efforts to devise distributed implementations of this algorithm. Recently, distributed adaptive CSMA scheduling schemes \cite{jiang08} have been proposed and shown to be optimal, without the need of message passing among transmitters. However their analysis relies on the assumption that interference can be accurately modelled by a simple interference graph. In this paper, we consider the more realistic and challenging SINR interference model. We present {\it the first distributed scheduling algorithms that (i) are optimal under the SINR interference model, and (ii) that do not require any message passing}. They are based on a combination of a simple and efficient power allocation strategy referred to as {\it Power Packing} and randomization techniques. We first devise algorithms that are rate-optimal in the sense that they perform as well as the best centralized scheduling schemes in scenarios where each transmitter is aware of the rate at which it should send packets to the corresponding receiver. We then extend these algorithms so that they reach throughput-optimality

Controlo de congestionamento em redes sem fios

Doutoramento em Engenharia ElectrotécnicaCongestion control in wireless networks is an important and open issue. Previous research has proven the poor performance of the Transport Control Protocol (TCP) in such networks. The factors that contribute to the poor performance of TCP in wireless environments concern its unsuitability to identify/detect and react properly to network events, its TCP window based ow control algorithm that is not suitable for the wireless channel, and the congestion collapse due to mobility. New rate based mechanisms have been proposed to mitigate TCP performance in wired and wireless networks. However, these mechanisms also present poor performance, as they lack of suitable bandwidth estimation techniques for multi-hop wireless networks. It is thus important to improve congestion control performance in wireless networks, incorporating components that are suitable for wireless environments. A congestion control scheme which provides an e - cient and fair sharing of the underlying network capacity and available bandwidth among multiple competing applications is crucial to the definition of new e cient and fair congestion control schemes on wireless multi-hop networks. The Thesis is divided in three parts. First, we present a performance evaluation study of several congestion control protocols against TCP, in wireless mesh and ad-hoc networks. The obtained results show that rate based congestion control protocols need an eficient and accurate underlying available bandwidth estimation technique. The second part of the Thesis presents a new link capacity and available bandwidth estimation mechanism denoted as rt-Winf (real time wireless inference). The estimation is performed in real-time and without the need to intrusively inject packets in the network. Simulation results show that rt-Winf obtains the available bandwidth and capacity estimation with accuracy and without introducing overhead trafic in the network. The third part of the Thesis proposes the development of new congestion control mechanisms to address the congestion control problems of wireless networks. These congestion control mechanisms use cross layer information, obtained by rt-Winf, to accurately and eficiently estimate the available bandwidth and the path capacity over a wireless network path. Evaluation of these new proposed mechanisms, through ns-2 simulations, shows that the cooperation between rt-Winf and the congestion control algorithms is able to significantly increase congestion control eficiency and network performance.O controlo de congestionamento continua a ser extremamente importante quando se investiga o desempenho das redes sem fios. Trabalhos anteriores mostram o mau desempenho do Transport Control Proto- col (TCP) em redes sem fios. Os fatores que contribuem para um pior desempenho do TCP nesse tipo de redes s~ao: a sua falta de capacidade para identificar/detetar e reagir adequadamente a eventos da rede; a utilização de um algoritmo de controlo de uxo que não é adequado para o canal sem fios; e o colapso de congestionamento devido á mobilidade. Para colmatar este problemas foram propostos novos mecanismos de controlo de congestionamento baseados na taxa de transmissão. No entanto, estes mecanismos também apresentam um pior desempenho em redes sem fios, já que não utilizam mecanismos adequados para a avaliação da largura de banda disponível. Assim, é importante para melhorar o desempenho do controlo de congestionamento em redes sem fios, incluir componentes que são adequados para esse tipo de ambientes. Um esquema de controlo de congestionamento que permita uma partilha eficiente e justa da capacidade da rede e da largura de banda disponível entre múltiplas aplicações concorrentes é crucial para a definição de novos, eficientes e justos mecanismos de controlo congestionamento para as redes sem fios. A Tese está dividida em três partes. Primeiro, apresentamos um estudo sobre a avaliação de desempenho de vários protocolos de controlo de congestionamento relativamente ao TCP, em redes sem fios em malha e ad-hoc. Os resultados obtidos mostram que os protocolos baseados na taxa de transmissão precisam de uma técnica de avaliação da largura de banda disponível que seja eficiente e precisa . A segunda parte da Tese apresenta um novo mecanismo de avaliação da capacidade da ligação e da largura de banda disponível, designada por rt-Winf (real time wireless inference). A avaliação é realizada em tempo real e sem a necessidade de inserir tráfego na rede. Os resultados obtidos através de simulação e emulação mostram que o rt-Winf obtém com precisão a largura de banda disponível e a capacidade da ligação sem sobrecarregar a rede. A terceira parte da Tese propõe novos mecanismos de controlo de congestionamento em redes sem fios. Estes mecanismos de controlo de congestionamento apresentam um conjunto de caracter ísticas novas para melhorar o seu desempenho, de entre as quais se destaca a utilização da informação de largura de banda disponível obtida pelo rt-Winf. Os resultados da avaliação destes mecanismos, utilizando o simulador ns-2, permitem concluir que a cooperação entre o rt-Winf e os algoritmos de controlo de congestionamento aumenta significativamente o desempenho da rede

Resource allocation for wireless networks: learning, competition and coordination.

Lin, Xingqin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (p. 103-109).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.iiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.2 --- Background --- p.3Chapter 1.2.1 --- Wireless Communication Schemes --- p.3Chapter 1.2.2 --- Mathematical Preliminaries --- p.8Chapter 1.3 --- Outline of the Thesis --- p.12Chapter 2 --- Learning for Parallel Gaussian Interference Channels --- p.14Chapter 2.1 --- System Model and Problem Formulation --- p.16Chapter 2.2 --- Stochastic Algorithm for Learning --- p.18Chapter 2.2.1 --- Algorithm Design --- p.18Chapter 2.2.2 --- Convergence Analysis --- p.21Chapter 2.3 --- Continuous Time Approximation --- p.26Chapter 2.4 --- Learning with Averaging --- p.28Chapter 2.5 --- Numerical Results --- p.29Chapter 3 --- Power Control for One-to-Many Transmissions --- p.34Chapter 3.1 --- System Model --- p.35Chapter 3.2 --- A GNEP Approach --- p.38Chapter 3.2.1 --- Problem Formulation --- p.38Chapter 3.2.2 --- Preliminary Results --- p.39Chapter 3.3 --- Algorithm Design --- p.42Chapter 3.4 --- Numerical Results --- p.46Chapter 4 --- Flow Allocation in Multiple Access Networks --- p.50Chapter 4.1 --- System Model and Problem Formulation --- p.52Chapter 4.1.1 --- System Model --- p.52Chapter 4.1.2 --- Problem Formulation --- p.53Chapter 4.2 --- Characterization of NE --- p.57Chapter 4.2.1 --- Feasibility Assumption --- p.57Chapter 4.2.2 --- Existence and Uniqueness of NE --- p.58Chapter 4.3 --- Distributed Algorithms Design --- p.60Chapter 4.3.1 --- D-SBRA --- p.60Chapter 4.3.2 --- P-SBRA --- p.61Chapter 4.3.3 --- Best Response and Layered Structure --- p.65Chapter 4.4 --- Performance Evaluation --- p.67Chapter 4.4.1 --- Protocol Evaluation --- p.67Chapter 4.4.2 --- Convergence and Performance --- p.69Chapter 4.4.3 --- Flow Distribution --- p.71Chapter 4.4.4 --- A Grid Network Simulation --- p.73Chapter 5 --- Relay Assignment in Cooperative Networks --- p.76Chapter 5.1 --- System Model and Problem Formulation --- p.77Chapter 5.1.1 --- Three-Node Relay Model --- p.77Chapter 5.1.2 --- Network Model --- p.78Chapter 5.1.3 --- Problem Formulation --- p.78Chapter 5.2 --- Centralized Scheme --- p.80Chapter 5.2.1 --- Generalized Relay Assignment --- p.80Chapter 5.2.2 --- Admission Control --- p.83Chapter 5.2.3 --- Iteration Algorithm and Some Remarks --- p.84Chapter 5.3 --- A Simple Distributed Algorithm --- p.84Chapter 5.4 --- Numerical Results --- p.86Chapter 6 --- Conclusions and Future Work --- p.88Chapter 6.1 --- Conclusions --- p.88Chapter 6.2 --- Future Work --- p.89Chapter A --- Proof of Theorem 21 --- p.93Chapter B --- Proof of Theorem 22 --- p.96Chapter C --- Proof of Proposition 31 --- p.98Chapter D --- Proof of Proposition 44 --- p.101Bibliography --- p.10