Optimized Approach for Localization of Sensor Nodes in 2D Wireless Sensor Networks Using Modified Learning Enthusiasm-Based Teaching–Learning-Based Optimization Algorithm

Wireless Sensor Networks (WSNs) have a wonderful potential to interconnect with the physical world and collect data. Data estimation, long lifespan, deployment, routing, task scheduling, safety, localization are primary performance difficulties for WSNs. WSNs made up of sensor nodes set minimal battery power monitor reveal occurrences in field. Detecting location is difficult task, but it crucial characteristic many WSN applications. Locating all efficiently obtain precise an occurrence critical challenge. Surveillance, animal monitoring, tracking moving objects, forest fire detection just few applications that demand determination. To cope challenges WSNs, there variety algorithms accessible literature. The goal this research use various optimization strategies solve problem. In work, modified learning enthusiasm-based teaching–learning-based (mLebTLBO) algorithm used 2D problem applying notion exclusive anchor node movable target nodes. A LebTLBO seeks increase overall efficiency by assessing exploration exploitation abilities. computational results technique outperforms others respect errors environment WSN.