吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (4): 1265-1273.doi: 10.13229/j.cnki.jdxbgxb20170524

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基于能量预测的分簇可充电无线传感器网络充电调度

董颖, 崔梦瑶, 吴昊, 王雨后   

  1. 吉林大学 通信工程学院,长春 130012
  • 收稿日期:2017-04-24 出版日期:2018-07-01 发布日期:2018-07-01
  • 作者简介:董颖(1971-),女,副教授,博士.研究方向:无线传感器网络.E-mail:dongying@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(61107040); 吉林省科技发展计划项目(20180101042JC).

Clustering wireless rechargeable sensor networks charging schedule based on energy prediction

DONG Ying, CUI Meng-yao, WU Hao, WANG Yu-hou   

  1. College of Communication Engineering, Jilin University, Changchun 130012, China
  • Received:2017-04-24 Online:2018-07-01 Published:2018-07-01

摘要: 为及时对可充电无线传感器网络中的“饥饿”节点补充能量,提出了一种基于预测的分簇低能量路径移动充电算法(CLP)。网络采用非均匀分簇的多跳路由协议,每个簇选取能量最低的节点作为簇头节点,移动充电车仅为簇头节点充电并收集簇内节点的能量信息。每次充电调度完成后,移动充电车将所收集的能量信息发送至基站,基站根据马尔科夫模型预测各簇内节点的能耗,以优化选取下一次的充电目标。仿真结果表明,采用CLP算法比旅行商问题(TSP)算法的网络效用提高约20%,数据传输能力提高约17%。

关键词: 通信技术, 可充电无线传感器网络, 能量预测, 非均匀分簇, 马尔科夫模型

Abstract: To timely complete the energy supply for the “hungry” sensors in Wireless Rechargeable Sensor Networks (WRSNs), a cluster and low-energy route mobile charging algorithm, called Clustering Low-energy access Prediction (CLP), is proposed based on energy prediction. The WRSN adopts the unequal clustering and multiple-hops routing protocol, and it chooses the node with the lowest energy in each cluster as the head node of that cluster. The mobile charger provides energy just for the cluster head nodes and collects the energy information of sensors of each cluster. After each round of the charging schedule, the mobile charger sends the energy message to the base station, and the base station adopts the Markov model to forecast the energy consumption of the sensors in each cluster in order to optimize the selection of charging target for next new charging schedule. Compared with TSP algorithm network, the results of the simulation show that CLP algorithm can improve the network utility by nearly 20%, and the ability of data transmission of nodes is increased by nearly 17%.

Key words: communication technology, wireless rechargeable sensor networks(WRSNs), energy prediction, unequal clustering, Markov model

中图分类号: 

  • TN92
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