摘要
异构传感器网络的部署问题较之同构传感器网络更为复杂,需要充分考虑节点的异构性带来的影响。采用粒子群算法对异构传感器网络进行部署,加入异构性适应策略,并改进了适应度函数,提出一种异构性适用的粒子群算法。仿真结果表明,相比于基本粒子群算法,所提算法有效避免了陷入局部最优次于全局最优的情况,并加快了收敛性,提高了一定的网络覆盖性能。
The deployment of heterogeneous sensor networks is more complex than that of the homogeneous sensor networks, for which the influence of the heterogeneity of nodes should be taken into full consideration. Particle swarm optimization algorithm is used for the deployment of heterogeneous sensor networks. By integrating the heterogeneity adaptability strategy and improving the fitness function, a new particle swarm optimization algorithm adaptive for heterogeneity is proposed. Simulation results show that： Compared with the basic particle swarm optimization algorithm, the proposed method can accelerate the convergence speed, improve the network coverage performance, and effectively avoid falling into the situation that the local optimum is inferior to the global optimum.
出处
《电光与控制》
北大核心
2017年第10期40-44,63,共6页
Electronics Optics & Control
基金
"十二五"装备预先研究项目(51305080301)
关键词
异构传感器网络
异构性适用
粒子群算法
heterogeneous sensor network
heterogeneity adaptability
particle swarm optimization algorithm
