Joint computation offloading and resource allocation in vehicular edge computing based on an economic theory: walrasian equilibrium

Abstract

Vehicular Edge Computing (VEC) is a new paradigm which improves the quality of service (QoS) of vehicular applications. However, in VEC networks, the computation resources of each VEC server are limited, and there are mismatches between the resources requested by vehicles and the resources that can be allocated by VEC servers, which increase the delays of completing computation tasks. To address the problem, in this paper, we jointly analyse the computation offloading and resource allocation based on the Walrasian equilibrium. Firstly, we analyze utilities of vehicles and VEC servers, and model the computation offloading and resource allocation as optimization problems considering delay constraints, respectively. Then, we convert the joint problem into a VEC networks welfare maximization problem. Based on the dual decomposition optimization method, we solve the problem and find the best strategies of vehicles and VEC servers, which means the state of Walrasian equilibrium. Moreover, we propose an algorithm with a fast convergence rate to find the solution of VEC Walrasian equilibrium. Simulation results demonstrate the effectiveness of the proposed analytical method and algorithm.