北京航空航天大学学报 ›› 2014, Vol. 40 ›› Issue (1): 10-17.

• 论文 • 上一篇    下一篇

基于活动预测和能耗均衡的WSN路由算法

汪成亮, 王强   

  1. 重庆大学 计算机学院, 重庆 400044
  • 收稿日期:2013-03-20 出版日期:2014-01-20 发布日期:2014-01-22
  • 基金资助:
    国家自然科学基金资助项目(61004112);中央高校基本科研基金资助项目(CDJZRI2180006)

Activity-aware & energy balance based routing protocol for wireless sensor networks

Wang Chengliang, Wang Qiang   

  1. College of Computer Science, Chongqing University, Chongqing 400044, China
  • Received:2013-03-20 Online:2014-01-20 Published:2014-01-22

摘要: 无线传感网络(WSN,Wireless Sensor Network)中节点触发与数据传输往往会呈现出某种活动模式,基于活动模式特性提出了基于活动的节点分簇算法(AACP,Activity-Aware Clustering Protocol),将网络中的传感器 节点分成多个活动簇,并通过对节点的历史触发数据进行分析,结合分簇结果对当前发生的活动进行预测.基于活动预测结果,综合能耗均衡、节点剩余能量、传输能耗等影响因素,提出了基于活动预测和能耗均衡的WSN路由算法(AEBRP,Activity-aware and Energy Balanced Routing Protocol).仿真实验中与低功耗自适应集簇分层型协议(LEACH,Low Energy Adaptive Clustering Hierarchy)、基于跟踪的动态节点分簇算法(HCMTT,Hybrid Clustering for Multitarget Tracking in wireless sensor networks)和传感器信息系统中的高能效采集算法(PEGASIS,Power Efficient Gathering in Sensor Information System)进行比较,验证了AEBRP算法在维持网络能耗均衡、延长网络生命周期方面具有明显优势.

Abstract: The node triggering and data transmission in wireless sensor network(WSN) shows an activity pattern. A clustering algorithm activity-aware clustering protocol(AACP) was put forward based on this activity pattern. Sensor nodes were divided into a plurality of clusters by AACP, and then activities were predicted with clustering results and nodes' historical trigger data. Based on this predication and some other impacts, including energy balance, nodes' residual energy and transmission consumption, activity-aware and energy balanced routing protocol(AEBRP) was proposed. The real trigger data were used for simulation experiments to compare AEBRP with protocols low energy adaptive clustering hierarchy(LEACH), hybrid clustering for multitarget tracking in wireless sensor networks(HCMTT) and power efficient gathering in sensor information system(PEGASIS). The experimental results show that AEBRP has obvious advantages in maintaining the balance of energy consumption and prolong the network life cycle.

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