面向三维的有向异构传感器网络覆盖优化算法

Coverage optimization algorithm for three-dimensional directional heterogeneous sensor network

针对面向三维的有向异构传感器网络随机部署节点产生的覆盖重叠区和盲区的问题,提出了一种基于粒子群优化(PSO)算法面向三维的有向异构传感器网络覆盖优化算法(PSOTDH)。该算法在建立新的三维有向感知模型的基础上,在模型中引入三维重叠质心、三维有效质心和三维边界质心的概念,通过PSO算法对面向三维的有向异构传感器网络进行三维覆盖重叠区域优化和三维边界节点优化处理,使节点的主传感方向发生改变,从而使三维重叠质心、三维有效质心和三维边界质心分布更加均匀,进而达到提高覆盖率的目的。仿真结果表明,该算法经过25次优化以后可以提高网络覆盖率约27.82%。由此可见,该算法能够快速、有效地提高网络的覆盖率。

Concerning the coverage overlapping areas and blind spots caused by random deployment of nodes in three- dimensional directional heterogeneous network, a Particle Swarm Optimization （PSO） based coverage optimization algorithm for three-dimensional directional heterogeneous network, namely PSOTDH, was proposed. Through involving the concepts of three-dimensional overlapping centroid, three-dimensional effective eentroid and three-dimensional boundary centroid, three- dimensional overlapping area, and three-dimensional boundary nodes were optimized in a new three-dimensional directed perception model by using PSO. The sensing directions of the nodes were changed by PSOTDH, which made the distribution of three-dimensional overlapping centroids, three-dimensional effective centroids and three-dimensional boundary centroids more uniform, and achieved the purpose of improving coverage. Simulation results show that the proposed algorithm can improve coverage rate by about 27.82% after 25 iterations, which means the proposed algorithm can improve the coverage rate quickly and effectively.