基于Delaunay图的人工蜂群算法在WSN覆盖策略中的优化研究

Optimization of Artificial Bee Colony Algorithm Based on Delaunay Graph in WSN Coverage Strategy

传统的人工蜂群算法在应用于无线传感器网络覆盖时,虽然可以提高网络覆盖率,但是其后期收敛速度慢和早熟收敛等缺点,大量的消耗时间和能量,也无法确保网络覆盖质量.为提高混合无线传感器网络的覆盖效率,提出一种基于Delaunay图的人工蜂群算法控制移动节点的部署策略.通过固定节点形成的Delaunay图先找出覆盖漏洞,估算覆盖漏洞面积并计算出移动节点即引领蜂的数量和初始位置,通过评价覆盖漏洞面积的大小确定侦查蜂的局部搜索空间.通过对不同算法的仿真结果分析表明:D-ABC提高了网络覆盖率,进行了混合无线传感器网络覆盖策略的优化.

The traditional artificial bee colony algorithm can improve the network coverage when it is applied to the coverage of wireless sensor networks. Though it can improve the network coverage, its shortcomings such as slow convergence, premature convergence, a lot of waste and energy consumption can not guarantee the quality of network coverage. In order to improve the coverage efficiency of hybrid wireless sensor networks, an artificial bee colony algorithm based on Delaunay graph is proposed to control the deployment strategy of mobile nodes. Firstly, coverage loopholes was found through the fixed node to form the Delaunay graph. Estimate the coverage of the vulnerability area and calculate the number of mobile nodes that lead the bee and the initial position. The local search space of the detection bee was determined by evaluating the size of the coverage vulnerability area. Through the analysis of the simulation results of different algorithms ,D-ABC improved network coverage and optimized the hybrid wireless net- work coverage strategy.