Network coded gossip with correlated data
Author(s)Haeupler, Bernhard; Cohen, Asaf; Avin, Chen; Medard, Muriel
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We design and analyze gossip algorithms for networks with correlated data. In these networks, either the data to be distributed, the data already available at the nodes, or both, are correlated. Although coding schemes for correlated data have been studied extensively, the focus has been on characterizing the rate region in static memory-free networks. In a gossip-based scheme, however, nodes communicate among each other by continuously exchanging packets according to some underlying communication model. The main figure of merit in this setting is the stopping time - the time required until nodes can successfully decode. While Gossip schemes are practical, distributed and scalable, they have only been studied for uncorrelated data. We wish to close this gap by providing techniques to analyze network coded gossip in (dynamic) networks with correlated data. We give a clean framework for oblivious network models that applies to a multitude of network and communication scenarios, specify a general setting for distributed correlated data, and give tight bounds on the stopping times of network coded protocols in this wide range of scenarios.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 2012 IEEE International Symposium on Information Theory Proceedings
Institute of Electrical and Electronics Engineers (IEEE)
Haeupler, Bernhard, Asaf Cohen, Chen Avin, and Muriel Medard. “Network Coded Gossip with Correlated Data.” 2012 IEEE International Symposium on Information Theory Proceedings (July 2012).