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Optimization of Rate Allocation with Distortion Guarantee in Sensor Networks

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3 Author(s)
Chun-Lung Lin ; Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan ; Chen-Lung Chan ; Jia-Shung Wang

Lossy compression techniques are commonly used by long-term data-gathering applications that attempt to identify trends or other interesting patterns in an entire system since a data packet need not always be completely and immediately transmitted to the sink. In these applications, a nonterminal sensor node jointly encodes its own sensed data and the data received from its nearby nodes. The tendency for these nodes to have a high spatial correlation means that these data packets can be efficiently compressed together using a rate-distortion strategy. This paper addresses the optimal rate-distortion allocation problem, which determines an optimal bit rate of each sensor based on the target overall distortion to minimize the network transmission cost. We propose an analytically optimal rate-distortion allocation scheme, and we also extend it to a distributed version. Based on the presented allocation schemes, a greedy heuristic algorithm is proposed to build the most efficient data transmission structure to further reduce the transmission cost. The proposed methods were evaluated using simulations with real-world data sets. The simulation results indicate that the optimal allocation strategy can reduce the transmission cost to 6~15% of that for the uniform allocation scheme.

Published in:

Parallel and Distributed Systems, IEEE Transactions on  (Volume:22 ,  Issue: 7 )

Date of Publication:

July 2011

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