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Optimization of Rate Allocation with Distortion Guarantee in Sensor Networks
July 2011 (vol. 22 no. 7)
pp. 1230-1237
Chun-Lung Lin, Tsing Hua University, Hsinchu
Chen-Lung Chan, Tsing Hua University, Hsinchu
Jia-Shung Wang, Tsing Hua University, Hsinchu
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\sim 15\% of that for the uniform allocation scheme.

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Index Terms:
Sensor networks, compression, rate-distortion allocation, distributed applications, optimization, transform coding.
Chun-Lung Lin, Chen-Lung Chan, Jia-Shung Wang, "Optimization of Rate Allocation with Distortion Guarantee in Sensor Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 22, no. 7, pp. 1230-1237, July 2011, doi:10.1109/TPDS.2010.159
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