Type II Fuzzy Logic Based Cluster Head Selection for Wireless Sensor Network

Wireless Sensor Network (WSN) forms an essential part of IoT. It is embedded in the target environment to observe physical parameters based on type application. nodes WSN are constrained by different features such as memory, bandwidth, energy, and its processing capabilities. In WSN, data transmission process consumes maximum amount energy than sensing sensors. So, diverse clustering aggregation techniques designed achieve excellent efficiency WSN. this view, current research article presents a novel Type II Fuzzy Logic-based Cluster Head selection with Low Complexity Data Aggregation (T2FLCH-LCDA) technique for The presented model involves two-stage aggregation. Initially, three input residual distance Base Station (BS), node centrality used T2FLCH CH cluster construction. Besides, LCDA which follows Dictionary Based Encoding (DBE) perform at CHs. Finally, aggregated transmitted BS where it achieves efficiency. experimental validation T2FLCH-LCDA was executed under scenarios position BS. results revealed that achieved efficiency, lifetime, Compression Ratio (CR), power saving compared methods.