异构无线传感器网络中多目标优化节点部署策略

针对异构无线传感器网络节点高密度部署和事件发生存在"热点区域"问题,以区域覆盖率最大和网络能耗最小为优化目标,提出了一种基于多目标优化的二进制粒子群算法,对节点部署进行多目标优化。该算法采用概率感知模型,引入强支配系数使得解分布均匀,结合Pareto最优解选择排序和基于自适应权重的适应度分配,进而获得异构节点部署解。仿真结果表明:该算法能对目标空间进行广泛搜索,与NSGA—Ⅱ算法相比,算法具有良好的收敛性,能有效地提高网络的覆盖率和降低网络能耗。

Node deployment strategy of multi-objective optimization for heterogeneous wireless sensor networks

An algorithm based on multi-objective optimization binary particle swarm is proposed to solve the problem of node high-density deployment and events existing "hot spots" in heterogeneous wireless sensor networks.Area coverage is maximum and energy consumption is minimum are the optimization goals.Probability sensing model is used and strong predominance coefficient is introduced to provide a good diversity,both pareto optimum solution sorting and adaptive weight fitness assignment methods are used in this algorithm to get heterogeneous wireless sensor network’s node deployment solutions.Compared with NSGA—Ⅱ,the algorithm has good astringency and effectively improve network coverage and reduce energy consumption.