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• W2949454902 abstract "In this paper, we consider a network communications problem in which multiple correlated sources must be delivered to a single data collector node, over a network of noisy independent point-to-point channels. We prove that perfect reconstruction of all the sources at the sink is possible if and only if, for all partitions of the network nodes into two subsets S and S^c such that the sink is always in S^c, we have that H(U_S|U_{S^c}) < sum_{iin S,jin S^c} C_{ij}. Our main finding is that in this setup a general source/channel separation theorem holds, and that Shannon information behaves as a classical network flow, identical in nature to the flow of water in pipes. At first glance, it might seem surprising that separation holds in a fairly general network situation like the one we study. A closer look, however, reveals that the reason for this is that our model allows only for independent point-to-point channels between pairs of nodes, and not multiple-access and/or broadcast channels, for which separation is well known not to hold. This ``information as flow'' view provides an algorithmic interpretation for our results, among which perhaps the most important one is the optimality of implementing codes using a layered protocol stack." @default.
• W2949454902 created "2019-06-27" @default.
• W2949454902 creator A5029938544 @default.
• W2949454902 creator A5089850116 @default.
• W2949454902 date "2005-04-05" @default.
• W2949454902 modified "2023-09-27" @default.
• W2949454902 title "Network Information Flow with Correlated Sources" @default.
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• W2949454902 hasPublicationYear "2005" @default.
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