EEDCHS-PSO: Energy-Efficient Dynamic Cluster Head Selection with Differential Evolution and Particle Swarm Optimization for Wireless Sensor Networks (WSNS)

Abstract

The communication subsystem in WSNs is primarily responsible for energy consumption which becomes a consistent in the networks owing to the usage of non-rechargeable battery having a limited power supply. The technology of communicating through wireless mode is recommended in number of sensing applications as it is convenient to use affordable and reliable. Modern sensors are designed with compatibility to sense the factors of the environment and transfer them in wireless mode. The center which collects the information favor confined data that are being clustered from a set of sensors than gathering the data from individual sensors. In general, wireless sensor network (WSN) uses grouping algorithm for domestic and use in abroad for dynamic cluster head selection is considered to be a significant task. To resolve the issue of cluster head selection with greater coverage and balanced energy consumption during the formation of cluster, it is taken as an important aspect. In this formulated work, an efficient clustering algorithm is proposed for monitoring the environment called energy-efficient dynamic cluster head selection with particle swarm optimization (EEDCHS-PSO). The selection process of cluster heads (CHs) is carried depending on the calculation of ordinary transmission distance and lingering energy. It can be seen that the sensor nodes known as cluster head (CH) that performs the task to route the data from the cluster to the cluster head of other clusters or base stations. Proposed EEDCHS-DEBO shows better performance in energy competence, load balancing, and range of scale with low control overhead.