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Mobile Information Systems
Volume 6, Issue 3, Pages 229-247

Fault Reconnaissance Agent for Sensor Networks

Elhadi M. Shakshuki,1 Xinyu Xing,2 and Tarek R. Sheltami3

1Jodrey School of Computer Science, Acadia University Wolfville, Nova Scotia, Canada B4P 2R6
2Department of Computer Science, University of Colorado at Boulder, CO, USA
3Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

Received 15 September 2010; Accepted 15 September 2010

Copyright © 2010 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


One of the key prerequisite for a scalable, effective and efficient sensor network is the utilization of low-cost, low-overhead and high-resilient fault-inference techniques. To this end, we propose an intelligent agent system with a problem solving capability to address the issue of fault inference in sensor network environments. The intelligent agent system is designed and implemented at base-station side. The core of the agent system – problem solver – implements a fault-detection inference engine which harnesses Expectation Maximization (EM) algorithm to estimate fault probabilities of sensor nodes. To validate the correctness and effectiveness of the intelligent agent system, a set of experiments in a wireless sensor testbed are conducted. The experimental results show that our intelligent agent system is able to precisely estimate the fault probability of sensor nodes.