Optimization of wireless sensor network deployment based on desert golden mole optimization algorithm

The deployment of wireless sensor networks (WSNs) in extreme environments such as nuclear fusion devices and the aerospace industry is crucial for real-time monitoring of critical parameters. However, it faces many challenges. In this paper, we propose the desert golden mole optimization algorithm (DGMOA), a novel algorithm inspired by the survival strategy of the desert golden mole and combined with the Dingo optimization algorithm (DOA). DGMOA addresses these challenges through two core mechanisms: the sand swimming strategy enhances the global search capability, and the hiding strategy is used for fine-grained local optimization. Through simulation tests, DGMOA shows excellent performance. It can quickly explore a large range of solution space in the initial search phase and adjust the position of individuals to avoid local optimal traps, resulting in a more uniform sensor layout and higher coverage. In convergence speed, it outperforms existing algorithms with faster convergence. Regarding energy consumption, the reasonable node layout reduces unnecessary waste and prolongs the service life of the sensor network. The results show that DGMOA is a highly effective solution for sensor layout in complex and extreme environments, with significant improvements in performance and energy consumption over traditional methods.