Joint optimization of task offloading and resource allocation for UAV swarm-assisted edge computing systems
To improve the performance of unmanned aerial vehicle swarm-assisted edge computing systems under load imbalancing scenarios,a new unmanned aerial vehicle swarm edge computing system is constructed to improve the utilization of computing resources by using offloading data among unmanned aerial vehicle.The weighted sum of the system's delay and energy consumption are minimized by jointly optimizing the offloading scheme,deployment,and resource allocation of multiple unmanned aerial vehicle.The problem is highly nonconvex,and a two-layer optimization scheme is proposed to solve the problem,i.e.,the heuristic optimal evaluation algorithm.The upper layer uses a particle swarm algorithm to optimize the unmanned aerial vehicle locations.The lower layer uses a block coordinate descent algorithm to optimize the unmanned aerial vehicle data offloading and resource allocation under the determined locations.The simulation results show that the proposed scheme can effectively reduce the system cost and has obvious advantages over the benchmark strategies.
万方数据
维普
