上海交通大学学报(自然版) ›› 2017, Vol. 51 ›› Issue (6): 715-721.

• 兵器工业 • 上一篇    下一篇

基于虚拟力和果蝇优化算法混合控制水声传感器网络部署策略

 张颖,乔运龙,张海洋   

  1.  上海海事大学 信息工程学院, 上海 201306
  • 出版日期:2017-06-30 发布日期:2017-06-30
  • 基金资助:
     

 Coverage Enhancing for Underwater Acoustic Sensor Networks Based on
 Virtual Force and Fruit Fly Optimization Algorithm

 ZHANG Ying,QIAO Yunlong*,ZHANG Haiyang   

  1.  College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
  • Online:2017-06-30 Published:2017-06-30
  • Supported by:
     

摘要:  提出了基于改进的虚拟力和果蝇优化(Virtual Force and Fruit Fly Optimization,VFFO)算法混合控制水声传感器网络部署优化的方法.该方法首先通过虚拟力算法对传感器节点的初始部署进行优化,以得到较好的初始部署状态;然后通过改进的果蝇算法对水声传感器网络进行重部署,同时分析了算法的移动部署能耗问题.仿真结果表明,该算法在相同能耗下能够得到更高的网络有效覆盖率.

关键词:  , 水声传感器网络, 部署优化, 虚拟力, 果蝇优化算法

Abstract:  This paper proposes the virtual force and fruit fly optimization (VFFO) algorithm which consists of the improved virtual force and fruit fly optimization methods. The algorithm firstly optimizes the initial deployment by virtual force to get a better initial deployment status, then the improved fruit fly optimization algorithm is used to redeploy the sensor networks. Moreover, the energy consumption of the deployment is analysed. The simulation results show that the proposed algorithm can achieve a higher effective coverage rate with the same energy consumption.

Key words:  , acoustic sensor networks; deployment optimization; virtual force; fruit fly optimization algorithm

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