Distributed adaptation algorithms for rate-controlled video multicast over shared infrastructure networks

Authors:
Mohammad Rabby;Kaliappa Ravindran;Jun Wu
Affiliations:
Department of Computer Science, Graduate School and University Center, The City University of New York, New York, NY;Department of Computer Science, Graduate School and University Center, The City University of New York, New York, NY;Department of Computer Science, Graduate School and University Center, The City University of New York, New York, NY
Venue:
COMSNETS'10 Proceedings of the 2nd international conference on COMmunication systems and NETworks
Year:
2010

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Abstract

We consider a wide-area video conferencing application where the video sources can adapt their send rates according to the available bandwidth in the network paths. We advocate a joint rate control of the sources to relieve the congestion, instead of running multiple instances of a single-source adaptation algorithm and additively superposing their results. The existing techniques work nicely with single-source trees, but do not work optimally in the case of multisource trees with shared QoS goals. Using the well-known AIMD-based adaptation procedures, we incorporate the topology inferencing mechanism into a coordinated rate adaptation algorithm executed by the loss-experiencing sources. The paper provides a simulation based evaluation of our algorithm to corroborate the benefits.