Home > Research > Publications & Outputs > A decentralized control strategy for joint reso...
View graph of relations

A decentralized control strategy for joint resource allocation and routing in node-based wireless data networks

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Close
Publication date2012
Host publicationUltra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2012 4th International Congress on
Place of PublicationNew York
PublisherIEEE
Pages71-75
Number of pages5
ISBN (print)9781467320160
<mark>Original language</mark>English
Event4th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT) - St Petersburg, United Kingdom
Duration: 3/10/20125/10/2012

Conference

Conference4th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT)
Country/TerritoryUnited Kingdom
Period3/10/125/10/12

Conference

Conference4th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT)
Country/TerritoryUnited Kingdom
Period3/10/125/10/12

Abstract

The optimal performance of the network can be achieved by simultaneous optimization of routing and resource allocation. We use a delayed dynamic model of queue length in each node to describe the data flows in the network. Unlike similar previous works in the literature we assume that delay exists in the queuing model and so we will have dynamic flow model for the routing of data packets across the network. We assume that the capacity of a wireless link is a concave and increasing function of the communications resources allocated to the link, and the communications resources for groups of links are limited. With these assumptions we formulate the simultaneous routing and resource allocation (SRRA) problem as a convex optimization problem over the network flow variables and the communications variables. By our control strategy, an optimal routing performance in the presence of unknown network delays in network modeling and resource limitations is achieved.