Network Coded Gossip with Correlated Data
Bernhard Haeupler, Asaf Cohen, Chen Avin, Muriel M\'edard

TL;DR
This paper develops and analyzes gossip algorithms for networks with correlated data, providing tight bounds on their stopping times and extending the understanding of network coding in dynamic, correlated environments.
Contribution
It introduces a framework for analyzing network coded gossip with correlated data in dynamic networks, filling a gap in existing research.
Findings
Provided tight bounds on stopping times for correlated data gossip protocols.
Developed a versatile framework applicable to various network and communication models.
Extended analysis of network coding to dynamic, correlated data scenarios.
Abstract
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. This model is applicable for a variety of modern networks, such as sensor, peer-to-peer and content distribution networks. 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…
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Taxonomy
TopicsCooperative Communication and Network Coding · Wireless Communication Security Techniques · Mobile Ad Hoc Networks
