A Hybrid Swarm Optimization for Energy Efficient Clustering in Multi-hop Wireless Sensor Network

Wireless sensor network refers to distributed sets of embedded devices, all of them having processing units, wireless transmission interface and sensors or actuators. Data accumulation through effective network organizations helps nodes to be split into small sets known as clusters. This grouping of sensor nodes as clusters is known as clustering. All clusters have leaders known as cluster heads (CHs). Clustering networks for minimizing total distance is an NP-hard issue. For a particular network topology, it is hard to discover optimum quantity of cluster-heads as well as their positions. The current article suggests a hybrid differential evolution with multi objective bee swam optimization (MOBSO-DE) for efficient clustering. CH selection process is based on communication energy and factors like residual energy and energy constraint metric. Simulation shows that the new MOBSO-DE method outperformed LEACH and MOBSO for packet delivery ratio and network lifetime.