An Energy Efficient Clustering and Optimization Method for Data Aggregation in Wireless Sensor Networks

Abstract

A Wireless Sensor Network (WSN) is a smart network made up of tiny sensor nodes, a Base Station (BS), and a data center designed to collect system or environmental conditions such as humidity, temperature, air quality, and other variables. With the extensive usage of WSN technology, these networks are facing many challenges. As sensor nodes have limited energy resources and suffered from energy efficiency problems and complicated routing methods. The energy issues become challenging to manage the network's resources against multiple tasks for data sensing, transmission, and calculation for Cluster Head (CH) election and selection. The sensor nodes and CH nodes lie far from which consume more energy to transmit collected data towards their cause an extra load on node lie near BS. To solve this problem many researchers have proposed different CH selection or election schemes to mitigate the energy consumption for the data aggregation among the sensor nodes and CH nodes and BS. The existing solutions are used for CH selection in the cluster for data transmission toward the BS. With the energy efficiency, the network lifetime and throughput increased. Best route selection and improving energy efficiency is still a challenging task for existing protocols. This study proposed an Energy Efficient Clustering and Optimization Method. Data Aggregation (EECOM) for WSNs networks to address this issue. The CH is selected to the point lie near the energy focus point, and Gateway Node (GN) is selected in between the clusters to provide energy. Efficient route for data transmission to BS and to reduce the load on CH. BS is responsible for all calculations which efficiently counter the energy consumption issue.