摘要
提出一种混沌差分进化和动态逃逸粒子群的节点选择优化算法,通过混沌序列的均匀遍历特性和差分进化算法的高效全局搜索能力,对传感网络中的节点能量进行分类搜索,采用Logistics混沌映射对节点进行优化分区处理,将混沌扰动量融入节点能量分区过程中,获取最佳能量节点,利用动态逃逸粒子群方法,运算无线传感网络最佳能量节点的最优位置,实现网络节点覆盖优化。仿真结果说明,所提算法可增强无线传感网络最优节点的聚类性能,具有更好的无线传感器网络动态节点选择性能,并且收敛速度快,运算耗时少。
A chaos differential evolution and dynamic node selection of particle swarm optimization algorithm, through the chaotic sequence traversal features and efficient global searching ability of differential evolution algorithm, the sensor nodes in a network of energy to search classification, optimize the node partition using Logistics chaos mapping process, blend in chaos disturbance quantity node energy partition in the process, get the best energy node, using the method of dynamic escape particle swarm, optimal operation best energy wireless sensor network node location, optimized network nodes covered. The simulation result shows that the proposed algorithm can enhance the optimal node of wireless sensor network clustering performance, has better performance of wireless sensor network （WSN） dynamic node selection, and fast convergence speed, less operation time.
出处
《科技通报》
北大核心
2014年第5期141-144,共4页
Bulletin of Science and Technology
关键词
非密集
传感网络
节点
选择优化
the intensive a sensor network node choice to optimize the
