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Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks
Audience: Adults
Description: Wireless sensor networks are envisioned to consist of thousands of devices, each capable of some limited computation, communication, and sensing, operating in an unattended mode. According to a recent National Research Council report, the use of such networks of embedded systems "could well dwarf previous revolutions in the information revolution." To our knowledge, we are the first to propose a solution to the fault-event disambiguation problem in sensor networks. Our proposed solution, in the form of Bayesian fault recognition algorithms, exploits the notion that measurement error due to faulty equipment are likely to be uncorrelated, while environmental conditions are spatially correlated. We show through theoretical and simulation results that the optimal threshold decision algorithm we present can reduce sensor measurement faults by as much as 85-95 percent for fault rates up to 10 percent.

Keywords: Algorithms
Communication Networks
Sensor Networks
Duration: 1 hour or less
Fee: Greater than $500

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