Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking

Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking

Alonshia S. Elayaraja
Copyright: © 2019 |Pages: 14
DOI: 10.4018/978-1-5225-5522-3.ch001
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Abstract

Many applications in wireless sensor networks perform localization of nodes over an extended period of time. Optimal selection algorithm poses new challenges to the overall transmission power levels for target detection, and thus, localized energy optimized sensor management strategies are necessary for improving the accuracy of target tracking. In this chapter, a proposal plan to develop a Bayesian localized energy optimized sensor distribution scheme for efficient target tracking in wireless sensor network is designed. The sensor node localization is done with Bayesian average, which estimates the sensor node's energy optimality. Then the sensor nodes are localized and distributed based on the Bayesian energy estimate for efficient target tracking. The sensor node distributional strategy improves the accuracy of identifying the targets to be tracked quickly. The performance is evaluated with parameters such as accuracy of target tracking, energy consumption rate, localized node density, and time for target tracking.
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Existing systems for sensor node localization such as location anonymization algorithm (Chow et al, 2011), typically focus on aggregating k-anonymous locations with the aim of providing high quality location monitoring system. As an example, Trajectory-based data forwarding (Jeong et al, 2011) using link delay model develop a data forwarding scheme for light traffic vehicular ad hoc networks. A passive vehicular traffic measurement to increase sensor time synchronization error was designed in (Jeong et al, 2011) with the aid of autonomous passive localization algorithm.

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