Selection of Cluster Heads for Wireless Sensor Network in Ubiquitous Power Internet of Things


  • Wei Hu College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
  • Wenhui Yao College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
  • Yawei Hu College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
  • Huanhao Li College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China


Wireless sensor network (WSN), ubiquitous power internet of things (UPIoT), cluster head (CH) selection, clustering optimization


This paper designs a selection algorithm of cluster heads (CHs) in wireless sensor network (WSN) under the ubiquitous power Internet of Things (UPIoT), aiming to solve the network failure caused by premature death of WSN sensors and overcome the imbalance in energy consumption of sensors. The setting of the cluster head node helps to reduce the energy consumption of the nodes in the network, so the choice of cluster head is very important. The author firstly explains the low energy adaptive clustering hierarchy (LEACH) and the distance and energy based advanced LEACH (DEAL) protocol. Compared with the LEACH, the DEAL considers the remaining nodal energy and the sensor-sink distance. On this basis, the selectivity function-based CH selection (SF-CHs) algorithm was put forward to select CHs and optimize the clustering. Specifically, the choice of CHs was optimized by a selectivity function, which was established based on the remaining energy, number of neighbors, motion velocity and transmission environment of sensors. Meanwhile, a clustering function was constructed to optimize the clustering, eliminating extremely large or small clusters.Finally, the simulation proves that the DEAL protocol is more conducive to prolonging the life cycle of the sensor network. The SF-CHs algorithm can reduce the residual energy variance of nodes in the network, and the network failure time is later, which provides a way to improve the stability of the network and reduce energy loss.


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