A decentralized algorithm for the resource allocation in the mobile edge system of the Internet of Vehicles

The Internet of Vehicles (Iov) enables the sensing information collected by vehicles to be processed in a variety of ways, such as processed inside the vehicle or transmitted to roadside devices and cloud servers. That is a task computing and offloading problem in a mobile edge computing (MEC) system. This paper mainly studies the problem of competitive allocation of limited resources for multi-vehicle information processing and also studies the relationship between the total cost of the vehicles and some parameters such as the number of roadside devices. Based on real scenarios, we establish a multilevel vehicle internet sensor information service network composed of cloud servers, roadside devices, and in-vehicle devices. At the same time, we define a weighted cost model consisting of transmission delay and energy consumption. Combining the two models, the problem of competitive allocation of communication resources and computing resources is proposed, and the problem is transformed into a Multi-Individual Information Processing Game (MIIP-Game). Through the theory of game potential, we prove that there exists at least one NASH balanced solution in the MIIP game, and design a Total Cost Minimum Solving (TCMS) algorithm to find the best allocation method. Finally, the simulation experiments compare the strategy of TCMS with other strategies to verify the validity of the TCMS algorithm, and also investigate several ways to reduce the total cost.