Coding and control for communication networks

The purpose of this paper is to survey techniques for constructing effective policies for controlling complex networks, and to extend these techniques to capture special features of wireless communication networks under different networking scenarios. Among the key questions addressed are: The relat...

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Bibliographic Details
Published inQueueing systems Vol. 63; no. 1-4; pp. 195 - 216
Main Authors Chen, Wei, Traskov, Danail, Heindlmaier, Michael, Médard, Muriel, Meyn, Sean, Ozdaglar, Asuman
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.12.2009
Springer Nature B.V
Subjects
Approximation
Business and Management
Communication
Communications networks
Computer Communication Networks
Computer engineering
Control
Dynamic programming
Equilibrium
Operations Research/Decision Theory
Probability Theory and Stochastic Processes
Scheduling
Supply Chain Management
Systems Theory
Velocity
Workloads
94A05
Networks
Coding
90B15
90B18
Routing
Approximate dynamic programming
68M10
Scheduling
68M20
Information theory
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Summary:The purpose of this paper is to survey techniques for constructing effective policies for controlling complex networks, and to extend these techniques to capture special features of wireless communication networks under different networking scenarios. Among the key questions addressed are: The relationship between static network equilibria, and dynamic network control. The effect of coding on control and delay through rate regions. Routing, scheduling, and admission control. Through several examples, ranging from multiple-access systems to network coded multicast, we demonstrate that the rate region for a coded communication network may be approximated by a simple polyhedral subset of a Euclidean space. The polyhedral structure of the rate region, determined by the coding, enables a powerful workload relaxation method that is used for addressing complexity—the relaxation technique provides approximations of a highly complex network by a far simpler one. These approximations are the basis of a specific formulation of an h -MaxWeight policy for network routing. Simulations show a 50% improvement in average delay performance as compared to methods used in current practice.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0257-0130
1572-9443
DOI:10.1007/s11134-009-9148-3