Connectivity-based Delay Analysis in MEC-enhanced Vehicular Ad Hoc Networks

As one of the most critical parts of intelligent transportation systems (ITS), vehicular ad-hoc networks (VANET) has attracted extensive attention both in industry and academia. To cope with the explosive increments of vehicles and the mounting complexity of computing tasks, applying mobile edge computing (MEC) into VANET is an excellent solution. The connectivity probability and the delay are two critical performance metrics for measuring network quality. In this paper, we present the MEC-enhanced VANET architecture to help vehicles executing the computing tasks. The connectivity probability expressions of uplink and downlink in multi-hop of infrastructure based vehicular networks are deduced respectively. Based on the connectivity probability, the MEC offloading computing delay model is proposed. Moreover, the time delay of local computing and MEC offloading computing are compared and analyzed. Numerical results concluded from simulations are presented to give guidance for architecture deployment and resource management.