Research Analysis on Clustering Techniques in Wireless Sensor Networks

Modern technology relies heavily on wireless sensor networks (WSNs) since they have recently become essential components of the Internet of Things (IoT). Sensor nodes are part of WSNs, who collect data from surrounding areas as well as monitor the external environment. In a sensor network, clustering can be implemented to extend the battery life by reducing energy usage. So, the Clustering Algorithm is used to expose the core connection between the information without prior data and to additionally collects some information with shared characteristics into cluster. For WSN, there are a various clustering methods that differ in terms of Cluster Head selection, Cluster Selection, Data Aggregation Policy, Energy Efficiency, Inter Cluster and Intra Cluster Communication, and so on. The purpose of this paper is to present a list of density-based clustering methods, which have been proposed by different researchers in recent years.