Vehicular Cloud Computing: A cost-effective alternative to Edge Computing in 5G networks

2025-07-21

AI Summary

This work investigates the feasibility and technical-economic boundaries of vehicular cloud computing (VCC) as a cost-effective alternative to edge computing (EC) for supporting ultra-low-latency 5G applications, aiming to reduce infrastructure deployment and operational expenditures for network operators. Method: We propose the first systematic VCC–EC substitutability analysis framework, characterizing applicability conditions based on vehicle density, mobility patterns, workload dynamics, and resource availability. Leveraging co-simulation integrating SUMO (for realistic vehicular mobility modeling) and NS-3 5G-LENA (for accurate 5G radio access and core network emulation), we evaluate end-to-end latency, task success rate, and cost efficiency across large-scale urban and highway scenarios. Results: VCC effectively replaces EC for latency-critical applications with ≤50 ms requirements in typical urban and highway environments; EC remains indispensable only under stringent sub-16 ms constraints. This study quantifies, for the first time, the precise technical and economic boundaries under which VCC serves as a lightweight EC alternative—enabling low-latency service deployment without new infrastructure investment.

Technology Category

• Machine Learning: Learning on the Edge & Model Compression
• Planning, Routing, and Scheduling: Applications
• Application Domains: Mobility, Driving & Flight

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Sustainability and climate impact of web technologies

Abstract

Edge Computing (EC) is a computational paradigm that involves deploying resources such as CPUs and GPUs near end-users, enabling low-latency applications like augmented reality and real-time gaming. However, deploying and maintaining a vast network of EC nodes is costly, which can explain its limited deployment today. A new paradigm called Vehicular Cloud Computing (VCC) has emerged and inspired interest among researchers and industry. VCC opportunistically utilizes existing and idle vehicular computational resources for external task offloading. This work is the first to systematically address the following question: Can VCC replace EC for low-latency applications? Answering this question is highly relevant for Network Operators (NOs), as VCC could eliminate costs associated with EC given that it requires no infrastructural investment. Despite its potential, no systematic study has yet explored the conditions under which VCC can effectively support low-latency applications without relying on EC. This work aims to fill that gap. Extensive simulations allow for assessing the crucial scenario factors that determine when this EC-to-VCC substitution is feasible. Considered factors are load, vehicles mobility and density, and availability. Potential for substitution is assessed based on multiple criteria, such as latency, task completion success, and cost. Vehicle mobility is simulated in SUMO, and communication in NS3 5G-LENA. The findings show that VCC can effectively replace EC for low-latency applications, except in extreme cases when the EC is still required (latency < 16 ms).

Problem

• Can Vehicular Cloud Computing replace Edge Computing for low-latency applications?
• What conditions enable VCC to support low-latency without EC?
• Assessing feasibility of VCC substitution based on latency and cost.

Innovation

• Utilizes idle vehicular resources for computing
• Assesses VCC feasibility via extensive simulations
• Replaces Edge Computing in most latency scenarios