An Improved DV-Hop Algorithm Based on Artificial Fish Swarm Algorithm

Abstract

DV-Hop localization algorithm is the most commonly used node localization algorithm in wireless sensor networks, but it does not take into account the impact of average distance per hop in calculating the position of unknown nodes, resulting in reduced positioning accuracy. To solve this problem, a new AFSADV-Hop (Artificial Fish Swarm Algorithm DV-Hop) algorithm based on artificial fish swarm algorithm was proposed in this paper. As artificial fish swarm algorithm has a faster convergence rate and can solve nonlinear function optimization problem, it is used to solve the optimization of the average distance per hop, so the location error caused by the average distance per hop is reduced, so that it is closer to the actual value. The simulation results show that the improved algorithm can effectively improve the algorithm's accuracy and stability without increasing the hardware cost.