期刊文献+

基于BWAS_BM的移动代理路由算法研究

The Study of Mobile Agent Routing Algorithm Based on BWAS_BM
下载PDF
导出
摘要 在无线传感器网络中采用移动代理技术能有效减少冗余数据传输,降低节点能量消耗,延长网络的生存周期.针对无线传感器网络中移动代理路由问题,提出适合较小规模网络的网络数据收集模型;采用改进的最优最差蚁群算法,引入变异操作防止无效路径的产生,以适应无线传感器网络应用环境.仿真实验结果表明,改进后的蚁群算法提高了算法全局收敛速度并有效避免无效路径的产生. 在无线传感器网络中采用移动代理技术能有效减少冗余数据传输,降低节点能量消耗,延长网络的生存周期.针对无线传感器网络中移动代理路由问题,提出适合较小规模网络的网络数据收集模型;采用改进的最优最差蚁群算法,引入变异操作防止无效路径的产生,以适应无线传感器网络应用环境.仿真实验结果表明,改进后的蚁群算法提高了算法全局收敛速度并有效避免无效路径的产生.
作者 张胜 贺庆全
出处 《计算机研究与发展》 EI CSCD 北大核心 2011年第S2期152-157,共6页 Journal of Computer Research and Development
基金 航空科学基金项目(2009ZD56009)
关键词 无线传感器网络 移动代理 路由 最优最差 变异 wireless sensor networks mobile agent routing best-worst mutation
  • 相关文献

参考文献9

  • 1马骏,张健沛,杨静,程丽丽.改进型蚁群算法求解旅行Agent问题[J].北京邮电大学学报,2008,31(6):46-49. 被引量:7
  • 2叶宁,王汝传.无线传感器网络数据融合模型研究[J].计算机科学,2006,33(6):58-60. 被引量:9
  • 3Olivier R,Dominique M.An event-driven framework for the simulation of networks of spiking neurons. Proc of European Symposium on Artificial Neural Networks . 2003
  • 4Li Yongzhong,Xu Jing,Zhao Bo.A new mobile agent architecture for wireless sensor networks. Industrial Electronics and Applications . 2008
  • 5Qi Hairong,Xu Yingyue,Wang Xiaoling.Mobile-agent-based collaborative signal and information processing in sensor networks. Proc of the IEEE . 2003
  • 6Zahra E,Hossien M.Automata based energy efficient spanning tree for data aggregation in wireless sensor networks. 11th IEEE Singapore International Conference on Communication Systems (ICCS08) . 2008
  • 7Lang Tong,Qing Zhao,Srihari Adireddy.Sensor Networks With Mobile Agents. Proceedings of MILCOM . 2003
  • 8Chen M,Taekyoung K,Yong Y, et al.Mobile Agent Based Wireless Sensor Networks. JOURNAL OF COMPUTERS . 2006
  • 9Dorigo M,Maniezzo V,Colorni A.Ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics . 1996

二级参考文献18

  • 1Chryssis Georgioua, Kowalskib Dariusz R, Shvartsmanc Alexander A. Efficient gossip and robust distributed computation [ J ]. Theoretical Computer Science, 2005, 34(4) : 130-166.
  • 2Liu Yu-Hsin. Diversified local search strategy under scatter search framework for the probabilistic traveling salesman problem [ J ]. European Journal of Operational Research, 2008, 191(2): 332-346.
  • 3Amilkar Puris, Rafael Bello, Yailen Martinez, et al. Two-stage ant colony optimization for solving the traveling salesman problem[J]. Nature Inspired Problem-Solving Methods in Knowledge Engineering, 2007, 28 (4) : 307-316.
  • 4Hani Y, Amodeoa L, Yalaouia F, et al. Ant colony optimization for solving an industrial layout problem [ J ]. European Journal of Operational Research, 2007, 18(5) : 633-642.
  • 5Heinonen J, Petterssona F. Hybrid ant colony optimization and visibility studies applied to a job-shop scheduling problem [ J ]. Applied Mathematics and Computation, 2007, 187(2): 989-998.
  • 6Moizumi K. The mobile agent planning problem [ D]. Hanover: Thayer School of Engineering, Darmouth College, 1998.
  • 7Dorigo M, Di Caro G. Ant colony optimization: a new meta-heuristie [ C ]//Proceedings of the Evolutionary Computation. Washington DC: [s. n. ], 1999: 1470- 1477.
  • 8WooldridgeM.多Agent系统引论[M].北京:电子工业出版社,2003..
  • 9Akyildiz I F, Su W, Cayirci E, et al. A Survey on Sensor Networks [J]. IEEE Communications Magazine,2002: 40(8) : 102~114
  • 10Krishnamachari B, Estrin D,Wicker S. Modeling data-centric rowting in wireless sensor networks [R]. In: Proc. IEEE INFOCOM, 2002

共引文献13

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