Network correlated data gathering with explicit communication: NP-completeness and algorithms

We consider the problem of correlated data gathering by a network with a sink node and a tree-based communication structure, where the goal is to minimize the total transmission cost of transporting the information collected by the nodes, to the sink node. For source coding of correlated data, we co...

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Bibliographic Details
Published inIEEE/ACM transactions on networking Vol. 14; no. 1; pp. 41 - 54
Main Authors Cristescu, R., Beferull-Lozano, B., Vetterli, M., Wattenhofer, R.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2006
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN1063-6692
1558-2566
1558-2566
DOI10.1109/TNET.2005.863711

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Summary:We consider the problem of correlated data gathering by a network with a sink node and a tree-based communication structure, where the goal is to minimize the total transmission cost of transporting the information collected by the nodes, to the sink node. For source coding of correlated data, we consider a joint entropy-based coding model with explicit communication where coding is simple and the transmission structure optimization is difficult. We first formulate the optimization problem definition in the general case and then we study further a network setting where the entropy conditioning at nodes does not depend on the amount of side information, but only on its availability. We prove that even in this simple case, the optimization problem is NP-hard. We propose some efficient, scalable, and distributed heuristic approximation algorithms for solving this problem and show by numerical simulations that the total transmission cost can be significantly improved over direct transmission or the shortest path tree. We also present an approximation algorithm that provides a tree transmission structure with total cost within a constant factor from the optimal.
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ISSN:1063-6692
1558-2566
1558-2566
DOI:10.1109/TNET.2005.863711