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计算机工程 ›› 2019, Vol. 45 ›› Issue (2): 13-17. doi: 10.19678/j.issn.1000-3428.0049194

所属专题: 物联网专题

• 物联网专题 • 上一篇    下一篇

基于改进猫群算法的物联网感知层路由优化策略

陶亚男1,2,张军朝1,2,王青文1,2,张俊虎2,3   

  1. 1.太原理工大学 电气与动力工程学院,太原 030024; 2.山西省电气传动及物联网工程技术研究中心,太原 030024; 3.太原市城市照明管理处,太原 030024
  • 收稿日期:2017-11-06 出版日期:2019-02-15 发布日期:2019-02-15
  • 作者简介:陶亚男(1991—),女,硕士研究生,主研方向为物联网应用;张军朝(通信作者),高级工程师、博士;王青文,硕士研究生;张俊虎,高级工程师。
  • 基金资助:

    山西省重大科技专项(20131101029);2017年山西省研究生教育改革研究课题(2017JG25);横向科技项目(2013-1401-05-000313)。

Routing Optimizaton Strategy of IoT Perception Layer Based on Improved Cat Swarm Algorithm

TAO Ya’nan 1,2,ZHANG Junchao 1,2,WANG Qingwen 1,2,ZHANG Junhu 2,3   

  1. 1.College of Electrical and Power Engineering,Taiyuan University of Technology,Taiyuan 030024,China; 2.Engineering-Technology Research Center of Electric Drive and IoT in Shanxi,Taiyuan 030024,China; 3.Taiyuan City Lighting Management Office,Taiyuan 030024,China
  • Received:2017-11-06 Online:2019-02-15 Published:2019-02-15

摘要:

针对物联网感知节点能量受限造成的数据传输瓶颈问题,提出一种基于改进猫群算法的路由优化策略。通过对猫群优化算法进行改进,根据迭代次数、路径节点能量与适应度值动态调整猫的分配率、记忆池和惯性权重,使其具有动态自适应性。在生成路径时综合考虑路径剩余能量方差、节点能量、节点负载、节点间距离等因素,并引入备份路由思想,保证数据传输的实时性。仿真结果表明,该优化策略能够有效减少最优路径建立时间并均衡网络能耗,延长物联网感知层网络的生命周期。

关键词: 物联网, 路由优化, 猫群优化, 动态调整, 备份路径, 能耗均衡

Abstract:

Aiming at the bottleneck of data transmission caused by the energy limitation of sensor nodes in Internet of Things(IoT),this paper proposes a routing optimization strategy based on improved Cat Swarm Optimization(CSO).The cat swarm optimization algorithm is improved.Each cat changes its own MR,SMP and inertia weight dynamically in each iteration process based on the number of iterations,energy of the path nodes and fitness.When the path is generated,path residual energy variance,node energy,node load,node distance four factors are taken into account,and the idea of backup routing is introduced to ensure the real time.Simulation results show that the optimization strategy can effectively reduce the optimal path construction time and balance the network energy consumption,and prolong the life cycle of the perception layer network of the IoT.

Key words: Internet of Things(IoT), routing optimization, Cat Swarm Optimization(CSO), dynamic adjustment, backup path, energy consumption balance

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