Enhanced Clustering and Intelligent Mobile Sink Path Construction for an Efficient Data Gathering in Wireless Sensor Networks

Abstract

Energy utilization of sensor nodes is a significant challenge in wireless sensor network (WSN). Increasing the energy efficiency of the WSN is a considerable aspect of concern, as higher energy consumption of sensor nodes decreases the existence of the network. Therefore, the energy utilization of sensor nodes plays an essential role in improving the lifetime of the WSN. Many existing methods use static sinks and multi-hop routing for data gathering that can cause an energy-hole problem and inadequate data gathering. Recent studies show that clustering can minimize energy usage of sensor nodes and mobile data collector (MDC) is used to gather sensor data by regularly visiting the nodes to avoid a hotspot or energy-hole problem. Thus, the use of enhanced clustering approach and MDC can improve the data gathering efficiency and cut down the energy consumption of the WSN. In this study, we have developed a JayaX with local search module-based cluster head selection (JayaX-LSM-CHS) approach and cluster formation method and adopted an ant colony optimization (ACO)-based algorithm for an efficient data gathering. The performance of the proposed framework (PF) is validated and compared with the state-of-the-art algorithms, namely dynamic clustering with ant colony optimization (DC-ACO), improved clustering with particle swarm optimization (IC-PSO), and LEACH protocol. The experimental results indicate that the PF significantly enhances the lifetime of the WSN.