A Management Framework for Vehicular Cloudtoward Economic and Environmental Efficiency
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866912622191837184 |
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| author | Patanè, Rosario Araldo, Andrea Achir, Nadjib Boukhatem, Lila |
| author_facet | Patanè, Rosario Araldo, Andrea Achir, Nadjib Boukhatem, Lila |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_24946 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Management Framework for Vehicular Cloudtoward Economic and Environmental Efficiency Patanè, Rosario Araldo, Andrea Achir, Nadjib Boukhatem, Lila Computer Science and Game Theory Distributed, Parallel, and Cluster Computing 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. |
| title | A Management Framework for Vehicular Cloudtoward Economic and Environmental Efficiency |
| topic | Computer Science and Game Theory Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2509.24946 |