无线传感器网络区域覆盖的拟物拟人优化方法

建立了以节能为目标的无线传感器网络(WSN)区域覆盖优化模型,指出此模型是一个具有指数复杂度的NP问题,针对问题特点设计了三条拟物拟人策略,分别是“拟万有引力“模型、“拟库仑力“模型和“共同富裕“模型.以此为基础,设计了一个拟物拟人算法(QPQSA),此算法是一个基于节点局部信息的分布式迭代算法:仿真结果显示,对于边界复杂的目标区域,无线传感器网络可由随机初始覆盖出发,经过自组织移位调整和功率控制达到一个优化的覆盖方案,经过优化,网络寿命延长了45.03%,覆盖率从72.28%提高至98.79%.

Quasi-physical and Quasi-sociological Method for Optimizing the Area Covering of Wireless Sensor Network

An optimizing model is set up for the area covering problem of Wireless Sensor Network(WSN), which is a NP problem having exponent complicated degree. Three quasi-physical and quasi-sociological methods are designed for the problem, and they are quasi-gravitation model, quasi-coulomb force model, and common enrichment model. Based on the three models, a quasi-physical and quasi-sociological algorithm (QPQSA) is proposed, which is a distributed iteration algorithm based on the sensor nodes'' local information. The artificial result reveals that, to a target area having complex boundary, WSN can achieve an optimized covering from a random initial covering by self-organized shift and power control. After optimizing, the network life-span has lengthened 45.03%, the coverage rate is improved from 77.28% to 98.79%.