A Cluster Head Selection Method Comparison of DCHSM, DEEC, and LEACH on Wireless Sensor Network Using Voronoi Diagram

Abstract

The Dynamic Cluster Head Selection Method (DCHSM) is a method for analyzing the energy consumption of the sensor nodes, thereby reducing the battery usage time on the WSN and in the low energy adaptive clustering hierarchical algorithm (LEACH), the selection for the Cluster Head (CH) is based solely on a random comparison of numbers generated by the probability value obtained. However, the problem that arises is how to simulate the selection of a cluster head model on a wireless sensor network to consume energy more efficiently. The purpose of this study is to apply and simulate the CH model so that energy consumption can be more efficient and analyze the performance results of the Dynamic Cluster Head Selection compared to other cluster head selection methods, namely LEACH and distributed energy saving clustering (DEEC). This research was conducted by simulation and there are three main scenarios in the simulation in which the scenarios run DCHSM, DEEC, and LEECH in the same environment. Each simulation varies the number of nodes used in the environment, namely 100, 200, and 300, to observe the scalability of the DCHSM algorithm and how it relates to energy savings. When compared with LEACH & DEEC, the DCHSM test results from the distribution graph and active nodes in the 100-node test are 7.12% higher, because the total active nodes in DCSHM have increased significantly compared to LEACH & DEEC. Meanwhile, when testing on graphs of 200 and 300 nodes, DCHSM experiences a decrease in performance, this concluded that the DCHSM algorithm had a saturation point so that its performance could not be maximized on large scales.