Departmental Papers (ESE)

Abstract

We study the fair allocation of bandwidth in multicast networks with multirate capabilities. In multirate transmission, each source encodes its signal in layers. The lowest layer contains the most important information and all receivers of a session should receive it. If a receiver’s data path has additional bandwidth, it receives higher layers which leads to a better quality of reception. The bandwidth allocation objective is to distribute the layers fairly. We present a computationally simple, decentralized scheduling policy that attains the maxmin fair rates without using any knowledge of traffic statistics and layer bandwidths. This policy learns the congestion level from the queue lengths at the nodes, and adapts the packet transmissions accordingly. When the network is congested, packets are dropped from the higher layers; therefore, the more important lower layers suffer negligible packet loss. We present analytical and simulation results that guarantee the maxmin fairness of the resulting rate allocation, and upper bound the packet loss rates for different layers.

Document Type

Journal Article

Date of this Version

September 2005

Comments

Copyright 2005 IEEE. Reprinted from IEEE Transactions on Neural Networks, Volume 16, Issue 5, September 2005, pages 1279-1290.

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Keywords

Back pressure, maxmin fairnesss, multicast, scheduling

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Date Posted: 25 February 2006

This document has been peer reviewed.