DocumentCode :
941869
Title :
A Distributed Framework for Correlated Data Gathering in Sensor Networks
Author :
Yuen, Kevin ; Ben Liang ; Li, Baochun
Author_Institution :
Univ. of Toronto, Toronto
Volume :
57
Issue :
1
fYear :
2008
Firstpage :
578
Lastpage :
593
Abstract :
We consider the problem of correlated data gathering in sensor networks with multiple sink nodes. The problem has two objectives. First, we would like to find a rate allocation on the correlated sensor nodes such that the data gathered by the sink nodes can reproduce the field of observation. Second, we would like to find a transmission structure on the network graph such that the total transmission energy consumed by the network is minimized. The existing solutions to this problem are impractical for deployment because they have not considered all of the following factors: (1) distributed implementation; (2) capacity and interference associated with the shared medium; and (3) realistic data correlation model. In this paper, we propose a new distributed framework to achieve minimum energy data gathering while considering these three factors. Based on a localized version of Slepian-Wolf coding, the problem is modeled as an optimization formulation with a distributed solution. The formulation is first relaxed with Lagrangian dualization and then solved with the subgradient algorithm. The algorithm is amenable to fully distributed implementations, which corresponds to the decentralized nature of sensor networks. To evaluate its effectiveness, we have conducted extensive simulations under a variety of network environments. The results indicate that the algorithm supports asynchronous network settings, sink mobility, and duty schedules.
Keywords :
correlation methods; distributed algorithms; gradient methods; graph theory; optimisation; statistical analysis; wireless sensor networks; Lagrangian dualization; Slepian-Wolf coding; correlated data gathering problem; data correlation model; distributed algorithm; minimum energy data gathering; multiple sink nodes; network graph; optimization formulation; rate allocation; sensor networks; subgradient algorithm; Correlated data gathering; data aggregation; distributed algorithm; mathematical optimization; wireless sensor networks;
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2007.905243
Filename :
4358484
Link To Document :
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