Computation Offloading and Resource Allocation Based on Game Theory in Symmetric MEC-Enabled Vehicular Networks

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Abstract

Due to the rocketing development of the Internet of Vehicles (IoV), the growth of computing-intensive and latency-sensitive applications brings a challenge to individual vehicles with limited computing resources. The computation offloading technology provides a feasible solution to this issue. In this paper, a multi-tier symmetric Vehicle-to-Everything (V2X) network framework is proposed, which consists of vehicle nodes (VNs), mobile edge computing (MEC) servers and a cloud server to provide computation offloading services for user vehicles. In this symmetric system, besides local computation, tasks can be offloaded to VNs or MEC servers or cloud servers for processing. The computation offloading problem in this network framework is considered as a game based on game theory. Then, in order to achieve the Nash equilibrium (NE) in this game, a joint optimization of computation offloading and resource allocation (JOCORA) algorithm is proposed. The numerical simulations show that the JOCORA algorithm can improve the success probability of offloading and reduce the total latency. The JOCORA algorithm has a better performance compared to other methods.

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