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无线多媒体传感器网络中自导向目标覆盖的优化

Optimization of self-directed target coverage in wireless multimedia sensor network.

作者信息

Yang Yang, Wang Yufei, Pi Dechang, Wang Ruchuan

机构信息

College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China ; Department of Information Technology, Nanjing Radio and TV University, Nanjing City Vocational College, Nanjing, Jiangsu 210002, China.

College of Computer, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210003, China.

出版信息

ScientificWorldJournal. 2014;2014:416218. doi: 10.1155/2014/416218. Epub 2014 Jun 30.

Abstract

Video and image sensors in wireless multimedia sensor networks (WMSNs) have directed view and limited sensing angle. So the methods to solve target coverage problem for traditional sensor networks, which use circle sensing model, are not suitable for WMSNs. Based on the FoV (field of view) sensing model and FoV disk model proposed, how expected multimedia sensor covers the target is defined by the deflection angle between target and the sensor's current orientation and the distance between target and the sensor. Then target coverage optimization algorithms based on expected coverage value are presented for single-sensor single-target, multisensor single-target, and single-sensor multitargets problems distinguishingly. Selecting the orientation that sensor rotated to cover every target falling in the FoV disk of that sensor for candidate orientations and using genetic algorithm to multisensor multitargets problem, which has NP-complete complexity, then result in the approximated minimum subset of sensors which covers all the targets in networks. Simulation results show the algorithm's performance and the effect of number of targets on the resulting subset.

摘要

无线多媒体传感器网络(WMSN)中的视频和图像传感器具有定向视图和有限的传感角度。因此,使用圆形传感模型解决传统传感器网络目标覆盖问题的方法不适用于WMSN。基于所提出的视场(FoV)传感模型和FoV圆盘模型,目标与传感器当前方向之间的偏转角以及目标与传感器之间的距离定义了预期多媒体传感器如何覆盖目标。然后分别针对单传感器单目标、多传感器单目标和单传感器多目标问题,提出了基于预期覆盖值的目标覆盖优化算法。选择传感器旋转以覆盖落入该传感器FoV圆盘中每个目标的方向作为候选方向,并将遗传算法用于具有NP完全复杂度的多传感器多目标问题,从而得到覆盖网络中所有目标的近似最小传感器子集。仿真结果展示了该算法的性能以及目标数量对所得子集的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c437/4100281/9152c56c18a2/TSWJ2014-416218.001.jpg

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