Generic Edge Computing System for Optimization and Computation Offloading of Unmanned Aerial Vehicle

Abstract

Several Unmanned Aerial Vehicles (UAVs) offer ground equipment low-latency edge computing services. On the other hand, low-Earth orbit satellites offer all-encompassing cloud computing services. The officially stated joint optimization problem is a mixed nonlinear programming problem, leading to the development of a two-layer optimization technique. It is suggested that a particle swarm optimization (PSO) algorithm can be used in the upper layer of the algorithm along with genetic algorithm (GA) operators to optimize the UAV's deployment position. The greedy algorithm is applied to optimize the offloading of processing jobs in the lowest layer of the algorithm. The feasibility and effectiveness of the proposed strategy have been validated by numerous numerical simulation tests. The findings show that it is similar to other benchmark algorithms. The proposed approach can also reduce the usual job response time of the system.