PROJECT TITLE :
Network Coding Based Information Spreading in Dynamic Networks With Correlated Data
During this paper, we have a tendency to style and analyze data spreading algorithms for dynamic networks with correlated knowledge. In these networks, either the information to be distributed, the information already obtainable at the nodes, or both are correlated. Moreover, nodes' availability and connectivity is dynamic—a scenario typical for wireless networks. Our contribution is twofold. 1st, although coding schemes for correlated data are studied extensively, the main focus has been on characterizing the speed region in static networks. In an information spreading theme, however, nodes might communicate by continuously exchanging packets in line with some underlying communication model. The main figure of benefit is the stopping time—the time needed until nodes can successfully decode. While data spreading schemes, like gossip, are sensible, distributed, and scalable, they need solely been studied for uncorrelated information. We shut this gap by providing techniques to analyze network-coded info spreading in dynamic networks with correlated knowledge. Second, we have a tendency to provide a clean framework for oblivious dynamic network models that in explicit applies to a large number of wireless network and communication eventualities. We specify a general setting for the information model and give tight bounds on the stopping times of network-coded protocols in this wide selection of settings. En route, we tend to analyze the capacities seen by nodes under a network-coded info spreading protocol, a previously unexplored question. We have a tendency to conclude with intensive simulations, clearly validating the key trends and phenomena predicted in the analysis.
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