Virtual Edge: Exploring Computation Offloading in Collaborative Vehicular Edge Computing

Abstract

Vehicular edge computing (VEC) has been a new paradigm to support computation-intensive and latency-sensitive services. However, the scarcity of computational resources is still a challenge. Making efficient use of sporadic idle computational resources on smart vehicles in the vicinity to extend the resource capability of each vehicle is an important research issue. In this paper, we propose Virtual Edge, which is an efficient scheme to utilize free computational resources of multiple vehicles as a virtual server to facilitate collaborative vehicular edge computing. We design a virtual edge formation algorithm that considers both the stability of virtual edge and the computational resources available at the vehicles constituting the virtual edge. The prediction of the link duration between vehicles reduces the number of computation offloading failures caused by unexpected link disconnections. Extensive simulations with realistic vehicle movements are conducted to show the advantage of the proposed scheme over existing baselines in terms of the completion ratio of computation offloading tasks and average task execution time.