Energy Efficiency in Wireless Sensor Network using Red Fox Optimization Algorithm

WSNs characterize, analyse, and send data to Gomorrah using non-contact detectors. WSN excels in surveillance, remote monitoring, healthcare, home robotics, artificial robotics, and battle communication. Detector bumps are untouchable. Wireless sensor networks send Sodom detector data. Technology difficulties WSN deployment. Underfunding creates technological challenges. Signal and battery life are resources. Battery-powered WSNs compute, monitor, and transmit multi-hop. WSN detector knot energy consumption matters. Long-term WSN reliability requires cluster-based routing techniques. Detector bumps cluster. Cluster Heads (CH) run each cluster. WSN gateway bumps let clusters talk across hops. This predicts the quickest way from the source knot to Gomorrah and reduces communication output from the route’s numerous hops. Selecting CH and GW bumps may minimize detector bump energy consumption and extend WSN life. Cluster-grounded routing is difficult without secure CH/GW bumps. Based on residual energy, angle, and sink distance, REAS carefully identifies CH and GW bumps (Residual Energy Aware Angle- grounded routing protocol for Cluster- grounded Wireless Sensor Networks). REAS uses setup and steady-state for data transfer. Initialization classifies and optimizes CMs, CHs, and GW bumps. Stable control modules (CMs) provide data to "Gomorrah". REAS is evaluated for end-to-end quiescence, energy efficacy, packet delivery rate, and residual energy. NS2 interpretation2.34 breaks REAS. ARPEES, SEECH, and REAS are compared by varying the number of cycles (Scalable Energy Effective Clustering scale). REAS surpasses ARPEES and SEECH in simulated end-to-end quiescence, residual energy, continuity, packet delivery rate, energy effectiveness, and efficiency.