MEC-assisted End-to-End Latency Evaluations for C-V2X Communications

TL;DR

This paper evaluates how deploying Multi-access Edge Computing (MEC) in 5G networks can significantly reduce end-to-end latency for vehicle-to-everything communications, especially in safety-critical scenarios involving vulnerable road users.

Contribution

It provides a comprehensive simulation-based comparison showing MEC's effectiveness in lowering latency compared to traditional cloud-based architectures in C-V2X communications.

Findings

MEC deployment reduces E2E latency in C-V2X scenarios.

Simulation results favor MEC-assisted architecture over conventional cloud-based systems.

Significant latency improvements support MEC for safety-critical vehicular applications.

Abstract

The efficient design of fifth generation (5G) mobile networks is driven by the need to support the dynamic proliferation of several vertical market segments. Considering the automotive sector, different Cellular Vehicle-to-Everything (C-V2X) use cases have been identified by the industrial and research world, referring to infotainment, automated driving and road safety. A common characteristic of these use cases is the need to exploit collective awareness of the road environment towards satisfying performance requirements. One of these requirements is the End-to-End (E2E) latency when, for instance, Vulnerable Road Users (VRUs) inform vehicles about their status (e.g., location) and activity, assisted by the cellular network. In this paper, focusing on a freeway-based VRU scenario, we argue that, in contrast to conventional, remote cloud-based cellular architecture, the deployment of Multi-access Edge Computing (MEC) infrastructure can substantially prune the E2E communication latency. Our argument is supported by an extensive simulation-based performance comparison between the conventional and the MEC-assisted network architecture.