GAPSO-H: A hybrid approach towards optimizing the cluster based routing in wireless sensor network

Wireless Sensor Networks (WSNs) have left an indelible mark on the lives of all by aiding in various sectors such as agriculture, education, manufacturing, monitoring environment, etc. Nevertheless, because wireless existence, sensor node batteries cannot be replaced when deployed a remote or unattended area. Several researches are therefore documented to extend node's survival time. While cluster-based routing has contributed significantly address this issue, there is still room for improvement choice cluster head (CH) integrating critical parameters. Furthermore, primarily focus had been either selection CH data transmission among nodes. The meta-heuristic methods promising approach acquire optimal network performance. In paper, ‘CH selection’ and ‘sink mobility-based transmission’, both optimized through hybrid that consider genetic algorithm (GA) particle swarm optimization (PSO) respectively each task. robust behavior GA helps selection, whereas, PSO finding route sink mobility. It observed simulation analysis results statistics proposed GAPSO-H (GA based hybrid) method outperform state-of-art algorithms at levels performance metrics.