Distributed algorithms for resource allocation of physical and transport layers in wireless cognitive ad hoc networks

In this paper, by integrating together congestion control, power control and spectrum allocation, a distributed algorithm is developed to maximize the aggregate source utility and increase end-to-end throughput. Despite the inherent difficulties of non-convexity and non-separability of variables in...

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Vydané v:Wireless networks Ročník 17; číslo 2; s. 337 - 356
Hlavní autori: Guo, Songtao, Dang, Chuangyin, Liao, Xiaofeng
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Boston Springer US 01.02.2011
Springer Nature B.V
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ISSN:1022-0038, 1572-8196
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Abstract In this paper, by integrating together congestion control, power control and spectrum allocation, a distributed algorithm is developed to maximize the aggregate source utility and increase end-to-end throughput. Despite the inherent difficulties of non-convexity and non-separability of variables in the original optimization problem, we are still able to obtain a decoupled and dual-decomposable convex formulation by applying an appropriate transformation and introducing some new variables. The objective is accomplished by the interaction and coordination among three sub-algorithms of the algorithm through the congestion prices. The convergence properties of the three sub-algorithms are also proved. Simulation results illustrate several other desirable properties of the proposed algorithm, including the impacts of node mobility and path and packet losses on convergence and robustness. This work is a preliminary attempt towards a systematic approach to jointly designing a congestion control sub-algorithm and a power control sub-algorithm coupled with a spectrum allocation sub-algorithm.
AbstractList In this paper, by integrating together congestion control, power control and spectrum allocation, a distributed algorithm is developed to maximize the aggregate source utility and increase end-to-end throughput. Despite the inherent difficulties of non-convexity and non-separability of variables in the original optimization problem, we are still able to obtain a decoupled and dual-decomposable convex formulation by applying an appropriate transformation and introducing some new variables. The objective is accomplished by the interaction and coordination among three sub-algorithms of the algorithm through the congestion prices. The convergence properties of the three sub-algorithms are also proved. Simulation results illustrate several other desirable properties of the proposed algorithm, including the impacts of node mobility and path and packet losses on convergence and robustness. This work is a preliminary attempt towards a systematic approach to jointly designing a congestion control sub-algorithm and a power control sub-algorithm coupled with a spectrum allocation sub-algorithm.[PUBLICATION ABSTRACT]
In this paper, by integrating together congestion control, power control and spectrum allocation, a distributed algorithm is developed to maximize the aggregate source utility and increase end-to-end throughput. Despite the inherent difficulties of non-convexity and non-separability of variables in the original optimization problem, we are still able to obtain a decoupled and dual-decomposable convex formulation by applying an appropriate transformation and introducing some new variables. The objective is accomplished by the interaction and coordination among three sub-algorithms of the algorithm through the congestion prices. The convergence properties of the three sub-algorithms are also proved. Simulation results illustrate several other desirable properties of the proposed algorithm, including the impacts of node mobility and path and packet losses on convergence and robustness. This work is a preliminary attempt towards a systematic approach to jointly designing a congestion control sub-algorithm and a power control sub-algorithm coupled with a spectrum allocation sub-algorithm.
Author Dang, Chuangyin
Guo, Songtao
Liao, Xiaofeng
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  givenname: Chuangyin
  surname: Dang
  fullname: Dang, Chuangyin
  organization: Department of Manufacturing Engineering & Engineering Management, City University of Hong Kong
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  givenname: Xiaofeng
  surname: Liao
  fullname: Liao, Xiaofeng
  organization: High Performance Networking Research Center, College of Computer Science, Chongqing University
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Keywords Dual decomposition
Spectrum allocation
Power control
Convex optimization
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Congestion control
Cognitive ad hoc network
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SubjectTerms Access control
Algorithms
Communications Engineering
Communications networks
Computer Communication Networks
Control algorithms
Decomposition
Electrical Engineering
Engineering
IT in Business
Networks
Optimization
Sensors
Spectrum allocation
Studies
Traffic congestion
Wireless networks
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Title Distributed algorithms for resource allocation of physical and transport layers in wireless cognitive ad hoc networks
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