Incentive Offloading with Communication and Computation Capacity Concerns for Vehicle Edge Computing

Abstract

With the popularity of intelligent vehicles, computation-intensive vehicle tasks rise dramatically. Vehicle edge computing (VEC) is a promising technology that offloads overloaded computation tasks of intelligent vehicles to the edge. However, VEC servers are constrained by their available computation capacity while dealing with numerous tasks. To this end, we propose multi-party cooperation to complete vehicle task offloading. Computation-assisted vehicles (CAVs) with free resources assist VEC servers to offload Computation-required vehicles (CRVs), which enables computation resources of VEC servers and CAVs for CRVs’ task execution. To motivate positive participation of VEC servers and CAVs, we design a resource management and pricing mechanism by quantifying their gains and costs. Such design efficiently integrate and leverage the communication mode and computing mode among participants to describe their interactions, which composes two two-stage Stackelberg games. While Nash equilibrium (NE) for each Stackelberg game reaches, none of participants violates unilaterally. Simulation results demonstrate its effectiveness of the proposed model.

Supported by National Natural Science Foundation of China under Grant No. 61802216, National Key Research and Development Plan Key Special Projects under Grant No. 2018YFB2100303, Shandong Province colleges and universities youth innovation technology plan innovation team project under Grant No. 2020KJN011, Program for Innovative Postdoctoral Talents in Shandong Province under Grant No. 40618030001.