A Secure Data Offloading Strategy for UAV Wireless Networks Based on Improved Ant Colony Algorithms

The application of the concept of edge computing is inseparable from computational offloading technology, which is used to offload computational tasks generated by user end devices to a place with superior computing power and return the computational results to the local area, thus reducing the loss of local resources to a large extent. The objective of this paper is to investigate a secure data offloading strategy for UAV wireless networks based on an improved ant colony algorithm. The improved ant colony algorithm is used as a decision algorithm to implement a single offload for multiple tasks with the help of Matlab, and a continuous offload simulation system for multiple tasks and its visualisation is implemented with the help of techniques such as containers. Through controlled experiments, the effects of selection and variation behaviour on the performance of the algorithm are analysed, and the performance and benefits of the improved ant colony algorithm are analysed with reference to the genetic algorithm. Based on the experimental data, it can be seen that the improved ant colony algorithm performs better and its benefits gradually increase as the system runs.