Improved Clustering Optimization Algorithm for Wireless Sensor Network Energy Balance

doi:10.23940/ijpe.19.05.p21.14451452

Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (5): 1445-1452.doi: 10.23940/ijpe.19.05.p21.14451452

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Improved Clustering Optimization Algorithm for Wireless Sensor Network Energy Balance

Jinyu Li^* and Jun Li

School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China

Submitted on ;
Contact: * E-mail address: lijinyu@mail.lzjtu.cn
About author:Jinyu Li received her M.S. degree in computer software and theory in 2010. She is a teacher in the Department of Computer Science and Technology at Lanzhou Jiaotong University. Her research areas include intelligent computation and data mining; Jun Li received her Ph.D. in intelligent transportation and information systems engineering from Lanzhou Jiaotong University in 2018. She is a teacher in the Department of Computer Science and Technology at Lanzhou Jiaotong University. Her current research interests include intelligent computing methods.
Supported by:
This work was supported by the Foundation for Sci & Tech Research Project of Lanzhou (No. 2015-2-74) and the Natural Science Foundation of Gansu Province of China (No. 1506RJZA084).

Abstract

Abstract: To get over the limited energy of nodes and unbalanced energy consumption in wireless sensor networks (WSN), this paper puts forward a WSN clustering routing algorithm based on weight function timing. The algorithm was applied to build the weight function between node aggregation degree and residual energy. Then, the weight function was based on producing the timing time for all nodes. Both the iteration number and the energy consumption were reduced in cluster head selection. At the same time, the node energy consumption rate and the distance from the node to the sink node were taken into consideration. Next, the reasonable cluster head was chosen according to each node's weight function value and the timing time. In the periodic clustering process, the proposed algorithm removes the aggregation degree exchange between the nodes, thus reducing the network traffic and lowering the network energy consumption. Simulation results show that the algorithm achieves excellent cluster convergence and stable cluster size.

Key words: wireless sensor network (WSN), routing algorithm, timing of weight function, cluster head selection

Jinyu Li and Jun Li. Improved Clustering Optimization Algorithm for Wireless Sensor Network Energy Balance [J]. Int J Performability Eng, 2019, 15(5): 1445-1452.

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Improved Clustering Optimization Algorithm for Wireless Sensor Network Energy Balance

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