A jointly non-cooperative game-based offloading and dynamic service migration approach in mobile edge computing

With the increase in the use of compute-intensive applications, the demand to continuously boost the efficiency of data processing increases. Offloading the compute-intensive application tasks to the edge servers can effectively solve problems for resource-constrained mobile devices. However, the computation offloading may increase network load and transmission delay, which will influence the user experience. On the other hand, the unceasing distance change between the local device and edge server could also affect the service quality due to user mobility. This paper proposes the offloading and service migration methods for compute-intensive applications to deal with these issues. First, the fine-grained computation offloading algorithm based on a non-cooperative game is proposed. The overhead on both the local side and edge side is analyzed. Moreover, the service migration path selection based on the Markov decision process is proposed by considering user mobility, energy cost, migration cost, available storage, and bandwidth. The optimal service migration path is selected according to the Markov decision process, which can improve service quality. Experiment results show that our proposed offloading strategy performs better in reducing energy consumption by more than 10% and latency by more than 6.2%, compared with other baseline algorithms, and saving mobile device energy and reducing task response time, saving over 10% of time and energy consumption compared to similar algorithms. The proposed service migration scheme can reduce migration times and maintain a success rate of more than 90% while guaranteeing service continuity in a multi-user scenario.