Optimizing Task Offloading Migration Decisions: An Advantage Actor-Critic Approach

The paper presents a study on task offloading migration decisions. The aim is to minimize the total latency of the offloaded computational tasks. Actor-Critic algorithm was employed to solve the problem, and real world taxi traces were used to train and test the model. The results indicate that the scheme of only migrating to neighboring servers performs well compared with the scheme of only migrating to any server. The model has good average rewards and converges faster, and has a degree of generalization ability.