An SMDP-Based Resource Allocation in Vehicular Cloud Computing Systems

• Published in: IEEE transactions on industrial electronics (1982) Vol. 62; no. 12; pp. 7920 - 7928
• Main Authors: Zheng, Kan, Meng, Hanlin, Chatzimisios, Periklis, Lei, Lei, Shen, Xuemin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cloud computing; Computational modeling; Delays; Markov analysis; Mobile communication; resource allocation; Resource management; Safety; Semi-Markov Decision Process (SMDP); Stochastic models; Vehicles; Vehicular Cloud Computing (VCC); vehicular cloud computing (VCC); semi-Markov decision process (SMDP); Resource allocation
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2015.2482119

Vehicular ad hoc networks are expected to significantly improve traffic safety and transportation efficiency while providing a comfortable driving experience. However, available communication, storage, and computation resources of the connected vehicles are not well utilized to meet the service requirements of intelligent transportation systems. Vehicular cloud computing (VCC) is a promising approach that makes use of the advantages of cloud computing and applies them to vehicular networks. In this paper, we propose an optimal computation resource allocation scheme to maximize the total long-term expected reward of the VCC system. The system reward is derived by taking into account both the income and cost of the VCC system as well as the variability feature of available resources. Then, the optimization problem is formulated as an infinite horizon semi-Markov decision process (SMDP) with the defined state space, action space, reward model, and transition probability distribution of the VCC system. We utilize the iteration algorithm to develop the optimal scheme that describes which action has to be taken under a certain state. Numerical results demonstrate that the significant performance gain can be obtained by the SMDP-based scheme within the acceptable complexity.