期刊文献+

无线传感器网络栅栏覆盖改进 被引量:5

Improving barrier coverage in wireless sensor networks
原文传递
导出
摘要 栅栏覆盖是无线传感器网络中的研究热点,鉴于移动节点的高昂造价以及在移动过程中的巨大能耗,针对高效节能的修复栅栏漏洞问题进行研究.建立静止节点的权重图,并利用迪杰斯特拉算法(Dijkstra)寻找所需最少数目的移动节点和构建栅栏覆盖的最短路径.根据构建栅栏覆盖的最短路径和基于路径上的每个栅栏漏洞所需的最少移动节点,将栅栏漏洞划分为简单情况和一般情况,借助于最大权匹配算法(Kuhn-Munkres)求解移动节点的最短移动距离.仿真实验表明,所提出算法明显减少了移动节点的移动距离,实现了栅栏覆盖. Barrier coverage is a research hot topic in wireless sensor networks(WSNs).Due to the high cost of mobile sensors and the high energy consumption during the moving process,it is critial to address the problem with an energyefficient method to mend barrier gaps.Therefore,we design a weighted graph of stationary sensors,use the Dijkstra algorithm to search the minimum number of mobile sensors required,and construct the shortest path of stationary sensors.According to the requried number of mobile sensors,barrier gaps are divied into simple case and general case.Finally,the Kuhn-Munkres(KM)algorithm is used to solve the minimum movement of the mobile sensors problem.Simulation results show that the proposed algorithm can effectively improve barrier coverage and minimize the moving distance of mobile sensors.
作者 司鹏举 吴成东 纪鹏 楚好 于晓升 SI Peng-ju;WU Cheng-dong;JI Peng;CHU Hao;YU Xiao-sheng(Faculty of Robot Science and Engineering,Northeastern University,Shenyang 110004,China)
出处 《控制与决策》 EI CSCD 北大核心 2019年第5期1037-1042,共6页 Control and Decision
基金 国家自然科学基金项目(U1713216 61471110 61701101 61503274 61733003) 国家机器人重点专项项目(2017YFB1300900) 中央高校基本科研业务费专项项目(N160413002 N160404003) 辽宁省自然科学基金项目(2017010975-301) 辽宁省教育厅科技项目(L20150185) 沈阳市科研基金项目(17-87-0-00)
关键词 无线传感器网络 栅栏覆盖 栅栏漏洞 移动节点 最短路径 最大权匹配 wireless sensor networks barrier coverage barrier gaps mobile sensor shortest path maximum weighted matching
  • 引文网络
  • 相关文献

参考文献1

二级参考文献14

  • 1Wang B, Lim H B, Ma D. A survey of movement strategies for improving network coverage in wireless sensor networks[J]. Computer Communications, 2009, 32(13/14): 1427-1436.
  • 2Chen J M, Li J K, He S B, et al. Energy-efficient coverage based on probabilistic sensing model in wireless sensor networks[J]. IEEE Communication Letters, 2012, 14(9): 833-835.
  • 3Yang Q Q, He S B, Li J K, et al. Energy-efficient probabilistic area coverage in wireless sensor networks[J]. IEEE Trans on Vehicular Technology, 2015, 64(1): 367-377.
  • 4Wang X B, Han S H, Wu Y B, et al. Coverage and energy consumption control in mobile heterogeneous wireless sensor networks[J]. IEEE Trans on Automatic Control, 2013, 58(4): 975-988.
  • 5Kosar R, Onur E, Ersoy C. Redeployment based sensing holes mitigation in wireless sensor networks[C]. Proc of IEEE Wireless Communications and Networking Conf. Budapest, 2009: 1-6.
  • 6Ghosh A. Estimating coverage holes and enhancing coverage in mixed sensor networks[C]. Proc of the 29th Annual IEEE Int Conf on Local Computer Networks. Tampa, 2004: 68-74.
  • 7LiW. A novel graphic coverage hole description in wireless sensor networks[J]. IEEE Communications Letters, 2014, 18(12): 2205-2208.
  • 8Mei Y, Xian C, Das S, et al. Sensor replacement using mobile robots[J]. Computer Communications, 2007, 30(13): 2615-2626.
  • 9Senouci M R, Mellouk A, Assnoune K. Localized movement-assisted sensor deployment algorithm for hole detection and healing[J]. IEEE Trans on Parallel and Distributed Systems, 2013, 25(2): 1267-1277.
  • 10Wu C, Cheng L, Zhang Y. Node redeployment for effective prolong maintenance period in wireless sensor networks[J]. IEICE Trans on Communications, 2012, E95B(10): 3179-3186.

共引文献6

同被引文献52

引证文献5

二级引证文献9

;
使用帮助 返回顶部