SMDP Based Cross-Area Resource Management for Vehicular Cloud Networks

Recent years have witnessed the emerging concept of Vehicular Cloud Networks (VCN) with the development of Internet of Vehicles and cloud computing. There is a common phenomenon that the loads and resources of local clouds (LCs) in different regions are seriously unbalanced in dynamic VCN as LCs are confronted with the shortage of resources and vehicles are featured by high mobility. As a consequence, we propose a cross-area resource management scheme (CRMS) based on semi-Markov decision process (SMDP) to alleviate this problem. In this scheme, a service migration mechanism plays an imperative role, which the local cloud needs to take the service requests from both local and neighboring cloud into account when allocating computing resources that we focus on in this paper. Considering the impact of different types of service requests on system revenue, we obtain the optimal policy of resource allocation adaptively through SMDP to maximize the long-term expected reward. Numerical results show the performance of the proposed CRMS has been significantly improved.