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On Distributed Distortion Optimization for Correlated Sources

Cui, Tao and Ho, Tracey and Chen, Lijun (2007) On Distributed Distortion Optimization for Correlated Sources. In: 2007 IEEE International Symposium on Information Theory. IEEE , Piscataway, NJ, pp. 2731-2735. ISBN 978-1-4244-1397-3.

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We consider lossy data compression in capacity-constrained networks with correlated sources. We develop, using dual decomposition, a distributed algorithm that maximizes an aggregate utility measure defined in terms of the distortion levels of the sources. No coordination among sources is required; each source adjusts its distortion level according to distortion prices fed back by the sinks. The algorithm is developed for the case of squared error distortion and high resolution coding where the rate distortion region is known, and is easily extended to consider achievable regions that can be expressed in a related form. Our distributed optimization framework applies to unicast and multicast with and without network coding. Numerical example shows relatively fast convergence, allowing the algorithm to be used in time-varying networks.

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Additional Information:© 2007 IEEE. This work has been supported in part by DARPA grant N66001-06-C-2020, Caltech's Lee Center for Advanced Networking and a gift from Microsoft Research.
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Defense Advanced Research Projects Agency (DARPA)N66001-06-C-2020
Caltech Lee Center for Advanced NetworkingUNSPECIFIED
Microsoft ResearchUNSPECIFIED
Record Number:CaltechAUTHORS:20170425-162520744
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Official Citation:T. Cui, T. Ho and L. Chen, "On Distributed Distortion Optimization for Correlated Sources," 2007 IEEE International Symposium on Information Theory, Nice, 2007, pp. 2731-2735. doi: 10.1109/ISIT.2007.4557631
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:76928
Deposited By: Kristin Buxton
Deposited On:26 Apr 2017 01:34
Last Modified:15 Nov 2021 17:03

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