Enhancing Coverage Efficiency and Lifetime of Wireless Sensor Network by Bio-Inspired Hybrid Optimization

The Wireless sensor networks (WSNs) serve as important components for a wide range of uses, including components for a wide range of uses, including environmental monitoring, intelligent urban areas, and defence activities.. These networks collect and transmit data wireless, and their effectiveness depends on two key factors: coverage area and network lifetime. In order to improve coverage area, energy consumption, along with network connectivity in static WSNs, this research suggests a novel hybrid optimization technique termed Hybrid Flower Pollination Horse Herd Optimization (HFPHHO). This strategy combines the advantages of Flower Pollination Optimization (FPO) and Horse Herd Optimization (HHO) algorithms. We have proposed and implemented the HFPHHO algorithm with MATLAB 2023 to optimize sensor placement and network connections. The proposed HFPHHO algorithm is compared to established optimization algorithms like PSO, GWO, BAT, FPA, and HHO. Simulations authenticate the enhancement of coverage area by 38.44% over optimized and 7.60% over hybridized case and Network lifetime enhancement by 28.46% over optimized and 8.86% over hybridized case.