基于广义高斯随机混沌算法的AFSA在WSN覆盖中的研究

Study on AFSA based on generalized Gaussian random chaos algorithm on WSN coverage

如何能够进行更好的覆盖优化是目前无线传感器网络研究的热点。针对目前的传感覆盖模型没有考虑覆盖范围、成本和连通性的问题进行改进,在人工鱼群算法(AFSA)的基础上,对初始阶段对人工鱼群采用广义高斯分布,在觅食阶段采用混沌算法,使得个体分布更加合理,有效减少了聚群行为的时间。仿真结果表明,改进后的人工鱼群能够有效地提高节点的覆盖率,降低了网络消耗和成本,为传感覆盖优化提供了一种新的方法。

How to conduct better coverage optimization is the current hot topic of study on wireless sensor network. Directing at situations such as cost increase of network node coverage and fragile life cycle,the paper made improvement in problems of cost and connectivity aiming at current sensor coverage model hasn＇t taken coverage range into account. And then adopted generalized Gaussian distribution to artificial fish swarm in the initial stage,and chaos algorithm in foraging stage on the basis of artificial fish swarm algorithm（ AFSA）,making individual distribution more rational,thus having effectively reduced time of swarm behavior. Simulation result represents that the improved artificial fish swarm can effectively improve coverage rate of node,effectively lower network consumption and cost and provide a new method for sensor coverage optimization.