ADAPTIVE CLUSTERING FOR ENHANCEMENT OF THROUGHPUT IN A DISTRIBUTED WIRELESS SENSOR NETWORK

Abstract

Clustered networks are of great demand today which may serve for communication in a cooperative fashion for nowadays evolving internet of things. In cases like habitat monitoring the animal may be fixed up with the sensor which becomes mobile. Especially when moving in herds or flocks the scenario is viewed as an event moving in clusters. This work aims at serving for such cases and providing an adaptive clustering with the size of the cluster being varied. As the group head dies in one cluster the cluster members are being allocated to the nearby heads based on the threshold of energy in the Cluster heading nodes. It is shown that the throughput of the network increases as the uninterrupted data collection is sustained through this residual energy scheme of member allocation to the different cluster head.