Fault reconnaissance agent for sensor networks

  • Authors:
  • Elhadi M. Shakshuki;Xinyu Xing;Tarek R. Sheltami

  • Affiliations:
  • (Correspd. E-mail: elhadi.shakshuki@acadiau.ca) Jodrey School of Computer Science, Acadia University Wolfville, Nova Scotia, B4P 2R6 Canada;Department of Computer Science, University of Colorado at Boulder, CO, USA;Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

  • Venue:
  • Mobile Information Systems
  • Year:
  • 2010

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Abstract

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.