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Secure incentive mechanism for energy trading in computing force networks enabled internet of vehicles: a contract theory approach

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Abstract

The integration of generative artificial intelligence (GAI) and internet of vehicles (IoV) will transform vehicular intelligence from conventional analytical intelligence to service-specific generative intelligence, enhancing vehicular services. In this context, computing force networks (CFNs), capable of flexibly scheduling widespread, multi-domain, multi-layer, and distributed resources, can cater to the demands of the IoV for ultra-high-density computing power and ultra-low latency. In CFNs, the integration of GAI and IoV consumes enormous energy, and GAI servers need to purchase energy from energy suppliers (ESs). However, the information asymmetry between GAI servers and ESs makes it difficult to price energy fairly and distributed ESs and GAI servers constitute a complex trading environment where malicious ESs may intentionally provide low-quality services. In this paper, to facilitate efficient and secure energy trading, and supply for ubiquitous AIGC services, we initially introduce an innovative CFNs-based GAI energy trading system architecture; present an energy consumption model for AIGC services, cost model of ESs, and reputation evaluation model of ESs; and obtain utility functions of GAI servers and ESs based on contract theory. Then, we propose a secure incentive mechanism in IoV, including designing an optimal contract scheme based on contract feasibility conditions and a safety guarantee mechanism based on blockchain. Simulation results demonstrate the feasibility and superiority of our energy trading mechanism.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 92267301, Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Foundation under Grant No. CMYJY-202200536, Beijing Municipal Natural Science Foundation under Grant 4244067.

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Authors and Affiliations

  1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Wen Wen, Renchao Xie, Qinqin Tang & Tao Huang

  2. China Mobile Research Institute, Beijing, 100053, China

    Lu Lu & Yuexia Fu

  3. Purple Mountain Laboratories, Nanjing, 211111, China

    Renchao Xie & Tao Huang

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  1. Wen Wen
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  2. Lu Lu
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  3. Renchao Xie
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  4. Qinqin Tang
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  6. Tao Huang
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Correspondence to Lu Lu.

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Wen, W., Lu, L., Xie, R. et al. Secure incentive mechanism for energy trading in computing force networks enabled internet of vehicles: a contract theory approach. J Supercomput 80, 26061–26087 (2024). https://doi.org/10.1007/s11227-024-06369-2

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