Cluster based wireless sensor Network design for smart grid Applications

Abstract

Wireless Sensor Networks (WSNs) have been an excellent candidate for online monitoring and replacement for manual diagnosis. Because of their unique feature and the advantages, wireless sensor network-based smart grid monitoring has favoured like self-configuration, low cost, low power consumption and rapid deployment. Clustering is one of the essential methods for increasing the network lifetime in Wireless Sensor Networks (WSNs). A major challenge in WSN is to select appropriate cluster heads and it also includes a grouping of sensor nodes into clusters and electing Cluster Heads (CHs) for all the clusters. Each CH collects the data from the respective cluster nodes and forwards the aggregated data to the base station. Hence, it consumes more power than other nodes in a cluster. A tremendous challenging task in that clustering is to select suitable cluster heads. newlineIn WSN, the clustering process includes cluster head selection based on distance from the base station, distance from neighbor and residual energy, etc. However, up to now the impact of temperature rise has not been considered. Based on the previous related works, this research introduces a thermal aware solution based on combining Eigen centrality fuzzy cluster size Control and Spider Optimization Algorithm (SOA). Furthermore, an influence of temperature can be realized with the help of Received Signal Strength (RSS) and the number of packets received. The proposed clustering method is simulated in MATLAB R2018A and implemented in hardware testbed using Zigbee and Peripheral Interface Controller (PIC) microcontroller. Consequently, the result confirms the impact of thermal heat on CH selection control and also the prediction of the number of rounds. The results show that the proposed system has 38 % lifetime improvement, 27 % living node count increment and 31.5 % successful packet reception improvement than standard LEACH and Fuzzy Clustering Particle Swarm Optimization algorithm newline