Classification And Clustering Performances on The Protocol of The Wireless Sensor Network - Chimpanzee Leader Election Optimization

Abstract

Energy consumption in wireless sensor networks (WSN) is an important thing to note. The nature of real-time data transmission on the WSN forces the WSN to have a shorter lifespan. The existibility of WSN certainly requires a strategy that supports it. This paper aims to observe the performance of a wireless sensor network protocol - chimpanzee leader selection optimization (WSN-CLEO). This protocol has been shown to perform better than some hierarchical routing models at sink positions in the WSN field. The clustering of sensor nodes in this WSN consists of two models, namely clustering and classification. Clustering sensor nodes use an algorithm of chimpanzee leader election optimization (CLEO), while classification uses a threshold value of the distance between the sensor nodes and the base station (BS). However, in the grouping of classification, the threshold distance between the sensor nodes and the BS needs to be proven more efficient in WSN energy management. This comparison method uses several distance classification settings on the WSN -CLEO at 60 meters, 80 meters, and 100 meters. After grouping the sensor nodes, the next step is selecting the group leader. The results of the study show insignificant differences in energy efficiency between the first node dead (FND), half node dead (HND), and last node dead (LND) in the comparison of each scenario. However, they have different tendencies, especially in FND.