期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

WSNs中基于遗传算法移动信宿路径的优化

Genetic Algorithm-based Optimizing the Path of Mobile Sink for Wireless Sensor Networks
下载PDF
导出
摘要 通过移动信宿(Mobile Sink,MS)能够有效地提高数据效率。MS遍历无线传感网络(Wireless Sensor Networks,WSNs),并在一些驻留点(Rendezvous Points,RPs)位置上停留,收集RPs附近数据。而寻找RPs的位置是基于MS数据收集的基本问题。为此,提出基于遗传算法的搜索RPs算法(Genetic algorithm-based find RPs algorithm,GAFR),再利用这些RPs构建MS遍历路径,最大化数据收集量。仿真结果表明,与TSP算法相比,提出的GAFR算法在数据长度和数据收集时间方面具有显著优势。 For wireless sensor networks( WSNs),data collection using mobile sink( MS) is an efficient approach to collect data from sensor nodes( SNs). The MS has to go through the WSN and collect data from SNs by stopping at some predefined locations from where SNs are in its vicinity. Finding the number of such locations is a fundamental problem in the path design of a MS. Therefore,genetic algorithm-based find RPs algorithm( GAFR) is proposed in this paper. GAFR algorithm finds the optimal number and location of sojourn points which are used to design the tour of the MS in order to maximum the number of collecting data. The results obtained shows better performance of VLGA over TSP algorithm in terms of path length and data collection time of the MS.
作者 王继营 胡君 WANG Ji-yin;HU Jun(HuangHuai University,Henan Zhumadian,463000,China;Hunan University,Hunan Changsha 410004,China)
机构地区 黄淮学院 湖南大学
出处 《中国电子科学研究院学报》 北大核心 2019年第10期1011-1015,共5页 Journal of China Academy of Electronics and Information Technology
基金 湖南省教育厅科学研究项目(15C0612)
关键词 数据收集 移动信宿 遗传算法 驻留点 数据收集时间 Data collection Mobile sink Rendezvous Points Data collection time
分类号 TP393 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献2

二级参考文献38

  • 1Zhang Z.Routing in intermittently connected mobile ad hoc networks and delay tolerant networks:Overview and challenges.IEEE Communications Surveys & Tutorials,2006,8(1):24-37.[doi:10.1109/COMST.2006.323440].
  • 2Perkins C,Royer E.Ad-Hoc on-demand distance vector routing.In:Proc.of the IEEE WMCSA'99.Washington:IEEE Computer Society Press,1999.90-100.[doi:10.1109/MCSA.1999.749281].
  • 3Intanagonwiwat C,Govindan R,Estrin D.Directed diffusion:A scalable and robust communication paradigm for sensor networks.In:Proc.of the ACM MobiCom 2000.New York:ACM Press,2000.56-67.[doi:10.1145/345910.345920].
  • 4Biswas S,Morris R.Opportunistic routing in multihop wireless networks.ACM SIGCOMM Computer Communication Review,2004,34(1):69-74.[doi:10.1145/972374.972387].
  • 5Biswas S,Morris R.ExOR:Opportunistic routing in multi-hop wireless networks.In:Proc.of the ACM SIGCOMM 2005.New York:ACM Press,2005.133-143.http://www.sigcomm.org/sigcomm2005/paper-BisMor.pdf.
  • 6Rozner E,Seshadri J,Mehta Y,Qiu L.Simple opportunistic routing protocol for wireless mesh networks.In:Proc.of the IEEE WiMesh 2006.Washington:IEEE Computer Society Press,2006.48-54.[doi:10.1109/WIMESH.2006.288602].
  • 7Westphal C.Opportunistic routing in dynamic ad hoc networks:The OPRAH protocol.In:Proc.of the IEEE MASS 2006.Washington:IEEE Computer Society Press,2006.570-573.[doi:10.1109/MOBHOC.2006.278612].
  • 8Couto DD,Aguayo D,Bicket J,Morris R.A high-throughput path metric for multi-hop wireless routing.In:Proc.of the ACM/ IEEE MobiCom 2003.Washington:IEEE Computer Society Press,2003.134-146.[doi:10.1145/938985.939000].
  • 9Chachulski S,Jennings M,Katti S,Katabi D.Trading structure for randomness in wireless opportunistic routing.In:Proc.of the ACM SIGCOMM 2007.New York:ACM Press,2007.169-180.[doi:10.1145/1282427.1282400].
  • 10Zorzi M,Rao RR.Geographic random forwarding (GeRaF) for ad hoc and sensor networks:Multihop performance.IEEE Trans.on Mobile Computing,2003,2(4):337-348.[doi:10.1109/TMC.2003.1255648].

共引文献33

中国电子科学研究院学报
2019年 第10期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部