UAV Path Planning for Data Gathering of IoT Nodes: Ant Colony or Simulated Annealing Optimization

Abstract

Using UAVs is a promising solution for gathering information of the wireless IoT sensors in geographic areas. In this UAVs mission, due to battery-powered, the shortest possible path between sensors should be found. In this paper, two optimization methods including ant colony algorithm and simulated annealing algorithm are modeled in three-dimensional mode to compare the performance and execution time of these two methods in different size of sensors. The results shows the SA optimization can be performed faster than an ant colony optimization for benchmarks in which the number of sensors is less than 50.