计算机工程 ›› 2018, Vol. 44 ›› Issue (12): 150-155,162.doi: 10.19678/j.issn.1000-3428.0048730

• 移动互联与通信技术 • 上一篇    下一篇

基于蚁群算法的非均匀分簇水声传感网能量优化路由研究

王磊1,2,乔莉1,齐俊艳1,刘志中1   

  1. 1.河南理工大学 计算机科学与技术学院,河南 焦作 454000; 2.大连理工大学 海岸和近海工程国家重点实验室,辽宁 大连 116024
  • 收稿日期:2017-09-19 出版日期:2018-12-15 发布日期:2018-12-15
  • 作者简介:王磊(1977—),男,副教授,主研方向为网络控制、嵌入式系统、无线传感器网络;乔莉,硕士;齐俊艳、刘志中,副教授
  • 基金项目:

    国家自然科学基金青年基金(61300124);教育部产学研协同育人计划项目(201701069012);河南省重点科技攻关计划项目(152102210102);河南省基础前沿项目(132300410333);河南省教育厅高校重点科研计划项目(16A520052,15A520001);河南理工大学博士基金(B2013-040)

Research on Energy Optimization Routing of Non-uniform Clustering Underwater Acoustic Sensor Network Based on Ant Colony Algorithm

WANG Lei 1,2,QIAO Li 1,QI Junyan 1,LIU Zhizhong 1   

  1. 1.College of Computer Science and Technology,Henan Polytechnic University,Jiaozuo,Henan 454000,China; 2.Coastal and Offshore Engineering State Key Laboratory,Dalian University of Technology,Dalian,Liaoning 116024,China
  • Received:2017-09-19 Online:2018-12-15 Published:2018-12-15

摘要:

针对现有的水声传感网非均匀分簇路由协议在成簇和簇间数据转发阶段能量消耗过大的问题,设计一种非均等成簇及簇间路由耗能优化算法。根据节点所剩能量、到基站间隔和能耗因子等要素设定阈值公式,进而优化选举簇首并考虑节点入簇权值,有效均衡节点能量耗损。在簇间数据转发阶段引入改进的蚁群算法,利用启发函数计算簇节点能量、间距大小及跳数,并在信息素浓度中加入所剩能量百分比,从而平衡簇首能耗。实验结果表明,与经典的LEACH、EEUC和EEMUC算法相比,该算法能有效降低能量耗损,延长网络的生存周期。

关键词: 水声传感网络, 网络能耗, 信息素浓度, 蚁群算法, 生存周期

Abstract:

Aiming at the problem that the existing under water acoustic sensor network non-uniform clustering routing protocol consumes too much energy in the clustering and inter-cluster data transmitting phase,a solution to the unequal clustering and inter-cluster routing energy optimization is designed.The threshold formula is set according to the remaining energy of the node,the interval to the base station and the energy consumption factor,and the electoral cluster head is optimized and the weight of the node cluster is considered to effectively balance the node energy loss.An improved ant colony algorithm is introduced in the inter-cluster data transmitting stage.The energy,spacing and hop count of the cluster nodes are considered by the heuristic function,and the percentage of remaining energy is added to the pheromone concentration to balance the energy consumption of the cluster head.Experimental results show that compared with the classical LEACH,EEUC and EEMUC algorithm,the algorithm reduces the energy loss and extends the life cycle of the network as a whole.

Key words: underwater acoustic sensor network, network energy consumption, pheromone concentration, ant colony algorithm, life cycle

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