A Management Framework for Vehicular Cloudtoward Economic and Environmental Efficiency

2025-09-29

AI Summary

Vehicle-mounted Cloud Computing (VCC) faces deployment barriers due to the lack of quantitative validation of its economic viability and environmental sustainability under realistic urban scenarios. This paper addresses the fundamental question: “Can VCC simultaneously achieve economic feasibility and low-carbon benefits?” We propose the first multi-objective collaborative management framework integrating latency, energy consumption, carbon emissions, and revenue. Our contributions are twofold: (1) We jointly model urban vehicular mobility and 5G network dynamics to uniformly quantify both the economic cost and end-to-end carbon footprint of task processing; (2) We design an energy-aware dynamic scheduling algorithm and a cooperative-game-theoretic revenue-sharing mechanism to incentivize vehicle participation while ensuring fair multi-stakeholder benefits. Simulation results demonstrate that our framework achieves millisecond-level low-latency task offloading, effectively monetizes underutilized in-vehicle computing resources, and reduces CO₂ emissions by over 99% compared to conventional edge servers.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Game Theory and Economic Paradigms: Coordination and Collaboration
• Computer Vision: Multi-modal Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• 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

Vehicular Cloud Computing (VCC) leverages the idle computing capacity of vehicles to execute end-users' offloaded tasks without requiring new computation infrastructure. Despite its conceptual appeal, VCC adoption is hindered by the lack of quantitative evidence demonstrating its profitability and environmental advantages in real-world scenarios. This paper tackles the fundamental question: Can VCC be both profitable and sustainable? We address this problem by proposing a management scheme for VCC that combines energy-aware task allocation with a game-theoretic revenue-sharing mechanism. Our framework is the first to jointly model latency, energy consumption, monetary incentives, and carbon emissions within urban mobility and 5G communication settings. The task allocation strategy maximizes the aggregate stakeholder utility while satisfying deadlines and minimizing energy costs. The payoffs are distributed via a coalitional game theory adapted to dynamic vehicular environments, to prevent disincentivizing participants with potentially negative contributions. Extensive simulations demonstrate that our approach supports low-latency task execution, enables effective monetization of vehicular resources, and reduces CO2 emissions by more than 99% compared to conventional edge infrastructures, making VCC a practical and sustainable alternative to edge computing.

Problem

• Proposing a management framework for profitable and sustainable vehicular cloud computing
• Addressing lack of quantitative evidence for VCC profitability and environmental benefits
• Jointly modeling latency, energy consumption, monetary incentives and carbon emissions

Innovation

• Energy-aware task allocation for vehicular cloud
• Game-theoretic revenue-sharing mechanism for incentives
• Joint modeling of latency, energy, profit, emissions