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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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

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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

CLC Number: 

  • TN92
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