基于MCLP的WSN定位参考点选择算法

为了避免经验算法和SHARP算法的覆盖度低和可靠性差的缺点,采用最大覆盖布局模型(MCLP)对定位参考点的选择进行研究,并将贪婪随机自适应算法(GRASP)应用到该模型.在此基础上提出了以覆盖度为目标的基于覆盖理论的定位参考点选择算法(CRS).该算法从构造最大三角形布局开始,然后采用逐步扩散的方式为定位参考点选择位置.最后利用Matlab进行仿真实验.仿真实验结果显示在不需要增加额外硬件开销情况下,CRS算法以增加布局时间为代价增加了覆盖度.

On the Reference Node Selection Algorithm Based on MCLP in WSN

To get rid of the shortcoming of low coverage/reliability of both empirical algorithm and SHARP algorithm, the reference location nodes selected with the Maximum Coverage of the Layout Problem (MCLP) were investigated introducing the Greedy Random Adaptive Search Procedure (GRASP) into MCLP. Then, the Coverage based Reference node Selection (CRS) algorithm was proposed where a maximum triangular coverage should be laid out then spread over step by step so as to select the locations of reference nodes. The result of the simulation tested with Matlab showed that the CRS algorithm can make the coverage bigger at the cost of prolonging the time for layout without increasing extra overheads for hardware.