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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 7 , ISSUE 3 (September 2014) > List of articles


Bo Wu * / Yanpeng Feng * / Hongyan Zheng *

Keywords : Partially observable Markov decision processes, wireless sensor networks, target tracking, energy consumption, posterior belief, clustering algorithm.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 3, Pages 628-641, DOI:

License : (CC BY-NC-ND 4.0)

Received Date : 20-February-2014 / Accepted: 02-July-2014 / Published Online: 01-September-2014



In this paper, we propose a novel posterior belief clustering (PBC) algorithm to solve the tradeoff between target tracking performance and sensors energy consumption in wireless sensor networks. We model the target tracking under dynamic uncertain environment using partially observable Markov decision processes (POMDPs), and transform the optimization of the tradeoff between tracking performance and energy consumption into yielding the optimal value function of POMDPs. We analyze the error of a class of continuous posterior beliefs by Kullback–Leibler (KL) divergence, and cluster these posterior beliefs into one based on the error of KL divergence. So, we calculate the posterior reward value only once for each cluster to eliminate repeated computation. The numerical results show that the proposed algorithm has its effectiveness in optimizing the tradeoff between tracking performance and energy consumption.

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