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Deflection-Aware Tracking-Principal Selection in Active Wireless Sensor Networks
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DOI：10.1109/TVT.2012.2201188.png)
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摘要
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This paper addresses the problem of energy efficiency balanced with tracking accuracy in wireless sensor networks (WSNs). Specifically, we focus on the issues related to selecting tracking principals, i.e., the nodes with two special tasks: 1) coordinating the activities among the sensors that are detecting the tracked object's locations in time and 2) selecting a node to which the tasks of coordination and data fusion will be handed off when the tracked object exits the sensing area of the current principal. Extending the existing results that based the respective principal selection algorithms on the assumption that the target's trajectory is approximated with straight line segments, we consider more general settings of (possibly) continuous changes of the direction of the moving target. We developed an approach based on particle filters to estimate the target's angular deflection at the time of a handoff, and we considered the tradeoffs between the expensive in-node computations incurred by the particle filters and the imprecision tolerance when selecting subsequent tracking principals. Our experiments demonstrate that the proposed approach yields significant savings in the number of handoffs and the number of unsuccessful transfers in comparison with previous approaches.
Keyword:
Moving-object tracking
network coverage
principal selection
sensor network
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IF:
7.1
论文数:
1.8W
被引数:
6.6W
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