通信学报 ›› 2017, Vol. 38 ›› Issue (6): 1-9.doi: 10.11959/j.issn.1000-436x.2017124

• 学术论文 •    下一篇

基于网络覆盖和多目标离散群集蜘蛛算法的多移动agent规划

刘洲洲1,2,李士宁2   

  1. 1 西安航空学院电子工程学院,陕西 西安 710077
    2 西北工业大学计算机学院,陕西 西安 710072
  • 修回日期:2017-04-18 出版日期:2017-06-25 发布日期:2017-06-30
  • 作者简介:刘洲洲(1981-),男,陕西延安人,西北工业大学博士后,西安航空学院副教授,主要研究方向为无线传感器网络、智能优化算法和不确定性推理。|李士宁(1967-),男,陕西延安人,博士,西北工业大学教授、博士生导师,主要研究方向为智能计算、无线传感器网络。
  • 基金资助:
    国家自然科学基金资助项目(61601365);陕西省教育厅科研计划基金资助项目(16JK1395)

Multi mobile agent itinerary planning based on network coverage and multi-objective discrete social spider optimization algorithm

Zhou-zhou LIU1,2,Shi-ning LI2   

  1. 1 School of Electronic Engineering,Xi’an Aeronautical University,Xi’an 710077,China
    2 School of Computer Science,Northwestern Polytechnical University,Xi’an 710072,China
  • Revised:2017-04-18 Online:2017-06-25 Published:2017-06-30
  • Supported by:
    The National Natural Science Foundation of China(61601365);The Scientific Research Program Funded by Shaanxi Provincial Education Department(16JK1395)

摘要:

以agent负载能耗均衡度和网络总能耗为指标构建多移动agent协作规划模型,为了尽可能延长网络生存周期,给出基于网络覆盖率的节点休眠机制,在满足WSN网络覆盖率要求的同时,采用较少节点处于工作状态。根据多移动agent协作规划技术特点,设计融合Pareto最优解多目标离散群集蜘蛛算法(MDSSO),重新定义插值学习和变异交换粒子更新策略,并动态调整最优解集规模,以提高MDSSO算法多目标求解精度。实验仿真结果表明,该方法能够快速合理给出 WSN 多移动 agent 规划路径,而且与其他传统算法相比,网络总能耗降低了约15%,生存期提高了约23%。

关键词: 无线传感器网络, 移动代理, 网络覆盖, 群集蜘蛛优化算法, 协作规划

Abstract:

The multi mobile agent collaboration planning model was constructed based on the mobile agent load balancing and total network energy consumption index.In order to prolong the network lifetime,the network node dormancy mechanism based on WSN network coverage was put forward,using fewer worked nodes to meet the requirements of network coverage.According to the multi mobile agent collaborative planning technical features,the multi-objective discrete social spider optimization algorithm (MDSSO) with Pareto optimal solutions was designed.The interpolation learning and exchange variations particle updating strategy was redefined,and the optimal set size was adjusted dynamically,which helps to improve the accuracy of MDSSO.Simulation results show that the proposed algorithm can quickly give the WSN multi mobile agent path planning scheme,and compared with other schemes,the network total energy consumption has reduced by 15%,and the network lifetime has increased by 23%.

Key words: wireless sensor network, mobile agent, network coverage, social spider optimization algorithm, itinerary planning

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