Priority-based target coverage in directional sensor networks using a genetic algorithm
Priority-based target coverage in directional sensor networks using a genetic algorithm
复制标题
使用遗传算法在定向传感器网络中基于优先级的目标覆盖
DOI：
10.1016/j.camwa.2008.10.019
复制
发表时间：
2009-06-01
影响因子：
2.9
通讯作者：
Shen, Ruimin
中科院分区：
文献类型：
--
作者：
Wang, Jian;Niu, Changyong;Shen, Ruimin
传感器网络已经应用于各种各样的情况。最近，由方向传感器组成的方向传感器网络受到了关注。对于传统的目标覆盖问题，方向传感器有限的感知角度使其更具挑战性。此外，个别目标也可能与不同的优先事项相关联。考虑到定向传感器与目标之间的距离对感知质量的影响，提出了基于优先级的目标覆盖问题，力求选择满足指定优先级的最小定向传感器子集，使其能够监控所有目标。由于NP完全复杂性，最小子集的方向传感器近似使用遗传算法。仿真结果揭示了多个因素对所得到的子集的大小的影响。(c)2008爱思唯尔有限公司保留所有权利。
Sensor networks have been applied in a wide variety of situations. Recently directional sensor networks consisting of directional sensors have gained attention. As for the traditional target coverage problem, the limited sensing angle of directional sensors makes it even more challenging. Moreover, individual targets may also be associated with differentiated priorities. Considering the distance between the directional sensors and targets influences sensing quality, this paper proposes the priority-based target coverage problem and strives to choose a minimum subset of directional sensors that can monitor all targets, satisfying their prescribed priorities. Due to the NP-Complete complexity, the minimum subset of directional sensors is approximated by using a genetic algorithm. Simulation results reveal the effects of multiple factors on the size of the resulting subset. (c) 2008 Elsevier Ltd. All rights reserved.