WIRELESS SENSOR NETWORKS BASED ON IMPROVED DUNG BEETLE ALGORITHM

To address the limitations of traditional Dung Beetle Optimization (DBO) in the wireless sensor network coverage problem, specifically like low convergence speed and susceptibility to local optima, this paper proposes an optimization scheme based on the Improved DBO algorithm (IDBO). The algorithm combines three key strategies: first, a Logistic chaos initialization strategy is used to generate a more optimal initial solution; second, a Levy flight strategy is introduced to enhance the global search capability; and finally, the search process is further optimized by using a dynamic nonlinear convergence factor to adaptively adjust the search step size. With the above improvements, the algorithm is significantly improved in global search performance. Experiments on the CEC2005 benchmark suite show that IDBO outperforms similar algorithms and approaches the global optimum. Finally, at last, the proposed IDBO algorithm is applied to the wireless sensor network coverage optimization problem for simulation experiments. The simulation results show that the improved IDBO algorithm improves the coverage of the network nodes by 4.9% compared to the basic DBO algorithm and enhances the overall performance of the network with good practicality, stability and robustness.