OCVC: An Overlapping-Enabled Cooperative Vehicular Fog Computing Protocol

With increasing time-critical and computation-intensive tasks generated by mobile applications, vehicular fog computing (VFC) has emerged as a promising solution to relieve the overload on roadside units (RSUs) or cloud centers. In VFC, tasks are offloaded to vehicular fog nodes local to the client devices, which exploits the under-explored computational resources of nearby vehicles. In this article, we propose a novel cooperative vehicular fog computing architecture from an overlapping perspective, termed Overlapping-enabled Cooperative Vehicular fog Computing (OCVC) to fully utilize vehicular fog nodes' local potential resources. Different from traditional cooperative VFC architecture where each vehicle only works in one fog computing group at one time, the proposed OCVC architecture enables vehicles to participate in different computing groups simultaneously, and thus is able to fully exploit potential computational resources in an overlapping manner. In addition, we provide a distributed OCVC scheme to solve the complicated computing group formation, overlapping resource allocation, and task assignment problem by employing the overlapping coalition formation (OCF) game framework and a heuristic offloading algorithm. We conduct simulations for performance comparison in terms of diversified performance metrics and numerical results show that the proposed OCVC scheme performs better than other benchmarks under different conditions.

Automated summary

This article proposes a cooperative vehicular fog computing architecture called OCVC, which fully utilizes the potential resources of vehicular fog nodes to address the overload issue in computation-intensive tasks. Unlike traditional architectures, OCVC enables vehicles to participate in multiple computing groups simultaneously, utilizing resources in an overlapping manner. The article also presents a distributed OCVC scheme that employs the overlapping coalition formation game framework and a heuristic offloading algorithm to solve complex group formation, resource allocation, and task assignment problems, with simulation results showing better performance compared to other benchmarks.