Heterogeneous Clustering for Energy Optimization in Wireless Sensor Networks

Abstract

WSN depicts a collection of spatially distributed and committed sensors for monitoring and registering the physical condition of the environment. As the WSN is evolving continuously, it has become the rising area for research. There are extensive fields where WSN come into play like area tracking, health monitoring, environment, and earth sensing etc. The main aim of WSN is to increase the life cycle and time period of sensor nodes deployed in the network as they are non-rechargeable. Many factors are responsible for increasing the network lifecycle as residual energy, a distance of sensor node, topology over which network is designed etc. A lot of work has been done in this aspect. In this paper, we have given a solution which decides the Cluster Heads (CHs) using many factors: delay based on residual energy and other parameters, the standard deviation of residual energy of connected nodes, the standard deviation of residual energy of disconnected nodes, and the distance between nodes and respective CH. Initially, sets of CHs are chosen by comparing their energy with the average energy of the network. The final CHs are selected using fitness function comparison based on energy consumption and distance factors. The other sensor nodes connect with the nearest CHs. Results show that our proposed algorithm is outperformed to the base algorithm and LEACH protocol as we have compared using the number of dead nodes and residual energy of the network.