An Enhanced Network Node Localization Algorithm Using Improved Particle Swarm Optimization

In this paper, we present a network node localization algorithm utilizing an enhanced particle swarm optimization (PSO) technique and conduct performance comparisons with conventional DV-Hop methods. The algorithm employs strategic modifications to PSO's velocity update mechanism and inertia weight adaptation to achieve more precise node positioning, thereby enhancing network management and maintenance efficiency. We provide comprehensive implementation details featuring mathematical models with position update equations and fitness functions that evaluate localization accuracy through Euclidean distance calculations. The implementation includes key functions for particle initialization, neighbor discovery routines, and convergence criteria monitoring. Experimental results demonstrate significant improvements in localization precision and convergence speed compared to baseline methods, validating the algorithm's effectiveness and superiority. This research contributes valuable insights for practical applications of node localization algorithms and advances the development of network science through optimized computational approaches.