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

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.