Fuzzy with Metaheuristics Based Routing for Clustered Wireless Sensor Networks

Wireless sensor network (WSN) plays a vital part in real time tracking and data collection applications. WSN incorporates set of numerous nodes (SNs) commonly utilized to observe the target region. The SNs operate using an inbuilt battery it is not easier replace or charge it. Therefore, proper utilization available energy essential prolong lifetime WSN. In this study, effective Type-II Fuzzy Logic with Butterfly Optimization Based Route Selection (TFL-BOARS) has been developed for clustered TFL-BOARS technique intends optimally select cluster heads (CHs) routes Besides, (T2FL) distinct input parameters namely residual (RE), link quality (LKQ), trust level (TRL), inter-cluster distance (ICD) node degree (NDE) CHs construct clusters. Also, butterfly optimization algorithm based route selection (BOARS) derived optimal addition, BOARS computed fitness function three such as communication cost, delay. order demonstrate improved effectiveness prolonged WSN, wide-ranging simulation analysis was implemented experimental results reported supremacy technique.