摘要
针对目标跟踪物联网感知层节点动态部署的特点,在人工鱼群算法和虚拟力算法的基础上,设计了融入虚拟力影响的人工鱼群控制算法,给出了算法的参数自适应调整策略,该算法利用节点间的虚拟力来影响人工鱼的觅食行为和追尾行为,指导人工鱼群的进化过程,加快算法的收敛性。仿真实验结果显示,算法能快速有效地实现无线传感器网络节点的部署优化,与人工鱼群算法和虚拟力算法相比,该算法不仅全局寻优能力强,且收敛速度快,可有效提高网络覆盖率,优化网络性能。
This paper proposes a virtual force-directed artificial fish swarm algorithm, and applied this algorithm to Sensor Layer nodes deployment of Target tracking IOT. In this algorithm, the virtual force influence the foraging behavior and rear-end behavior of artificial fish, direct the moving and updating status of artificial fish for improving the convergence speed. Simulation results show that virtual force-directed artificial fish swarm algorithm has better performance on regional convergence and global searching ability than virtual force algorithm and artificial fish swarm algorithm, and it can implement dynamic sensor nodes deployment efficiently and rapidly.
出处
《无线互联科技》
2014年第5期10-12,14,共4页
Wireless Internet Technology
基金
安徽省教育厅自然科学基金(KJ2012B067)
安徽省优秀青年人才基金(2012SQRL241)
关键词
物联网
感知层节点
虚拟力
人工鱼群算法
部署策略
Internet of things
Sensor Layer Node
Virtual Force
Artificial fish-swarm algorithm
Deployment strategy