Context-aware opportunistic computing in vehicle-to-vehicle networks

Abstract Recent advancement in communication among smart devices, vehicular fog computing introduces new dimensions for delay-sensitive applications. The traditional computing paradigm to install edge locations is no longer viable due to incurred latency while decision making, especially in delay-sensitive applications. In this paper, we propose a vehicle-to-vehicle task offloading framework that allows vehicles to utilize computation resources available at nearby vehicles. The objective is to bring fog computing near vehicles to achieve computational efficiency and improve quality of service. To overcome mobility issues, we implement Context-aware opportunistic offloading schemes based on speed, direction, and locality of vehicles. The schemes are compared to random offloading mechanism in terms of efficiency, task completion, failure rate, workload distribution, and waiting time. The results demonstrate a significant reduction in failure rate up to 10% with more tasks completed on vehicles within direct communication range.