An Enhanced Distributed Clustering Methodology and Data Aggregation in Connecting Dissimilar Wireless Sensor Networks (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2019)
One of the major advantages of wireless sensor network is their ability to operate in unattended, harsh environments in which existing human-in-the-loop monitoring schemes are uncertain, inefficient and sometimes impossible. Therefore, wireless sensors are expected to be deployed randomly in thepredetermined area of interest by a relatively uncontrolled manner. Given the huge area to be covered, the short lifespan of the battery-operated wireless sensors and the possibility of having damaged sensor nodes during deployment, large population of sensors are expected in the majority of wireless sensor applications. In centralized clustering, the cluster head isfixed. The rest of the nodes in the cluster act as member nodes. In distributed clustering, the cluster head is not fixed. The cluster head keeps onshiftingformnodetonodewithintheclusteronthebasisofsomeparameters.Hybridclusteringisthecombinationofbothcentralizedclusteringanddistributed clustering mechanisms. This paper gives a brief overview on clustering process in wireless sensor networks and an enhanced distributed clustering methodology and data aggregation in connecting dissimilar wireless sensor Networks. The proposed method is compared with LEACH and HEED Clustering methods.