Game Theory Based Opportunistic Computation Offloading in Cloud-Enabled IoV

• Published in: IEEE access Vol. 7; pp. 32551 - 32561
• Main Authors: Liwang, Minghui, Wang, Jiexiang, Gao, Zhibin, Du, Xiaojiang, Guizani, Mohsen
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G cloud-enabled IoV; 5G mobile communication; Cloud computing; Computation offloading; Computational modeling; Device-to-device communication; Electronic devices; Game theory; Games; Idling; Internet of Vehicles; Mobile computing; Monte Carlo simulation; Performance evaluation; Pricing; Stackelberg equilibrium; Task analysis; vehicle-to-vehicle communication; Vehicles
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2897617

With the growing popularity of the fifth-generation (5G) wireless systems and cloud-enabled Internet of Vehicles, vehicular cloud has been introduced as a novel mobile device computing mode, which enables vehicles to offload their computation-intensive tasks to neighbors. In this paper, we first present a 5G cloud-enabled scenario of vehicular cloud computing where a vehicular terminal works either as a service provider with idle computation resources or a requestor who has a computation-intensive task that can be executed either locally or offloaded to nearby providers via opportunistic vehicle-to-vehicle communications. Then, we study the following issues: 1) how to determine the appropriate offloading rate of requestors; 2) how to select the most appropriate computation service provider; 3) how to identify the ideal pricing strategy for each service provider. We address the above-mentioned problems by developing a two-player Stackelberg-game-based opportunistic computation offloading scheme under situations involving complete and incomplete information that primarily considers task completion duration and service price. We simplify the former case into a common resource assignment problem with mathematical solutions. For the latter case, Stackelberg equilibriums of the offloading game are derived, and the corresponding existence conditions are concretely discussed. Finally, a Monte-Carlo simulation-based performance evaluation shows that the proposed methods can significantly reduce the task completion duration while ensuring the profit of service providers, thus achieving mutually satisfactory computation offloading decisions.