ABSTRACT The increasing number of applications based on the Internet of Things, as well as advances in wireless communication, information and communication technology, and mobile cloud computing, has allowed mobile users to access a wider range of resources when mobile. As the use of vehicular cloud computing has become more popular due to its ability to improve driver and vehicle safety, researchers and industry have a growing interest in the design and development of vehicular networks for emerging applications. Vehicle drivers can now access a variety of on demand resources en route via vehicular network service providers. The adaptation of vehicular cloud services faces many challenges, including cost, privacy, and latency. The contributions of this paper are as follows. First, we propose a game theory-based framework to manage on-demand service provision in a vehicular cloud. We present three different game approaches, each of which helps drivers minimize their service costs and latency, and maximize their privacy. Second, we propose a quality-of-experience framework for service provision in a vehicular cloud for various types of users, a simple but effective model to determine driver preferences. Third, we propose using the trusted third party concept to represent drivers and service providers, and ensure fair game treatment. We develop and evaluate simulations of the proposed approaches under different network scenarios with respect to privacy, service cost, and latency, by varying the vehicle density and driver preferences. The results show that the proposed approach outperforms conventional models, since the game theory system introduces a bounded latency of ≤3%, achieves service cost savings up to 65%, and preserves driver privacy by reducing revealed information by up to 47%.
e Multiobjective Vehicular Interaction Game (MVIG) scheme REF proposes a new game theoretic scheme to control the on-demand service provision in a vehicular cloud.
Multiagent/multiobjective interaction game system for service provisioning in vehicular cloud
IEEE Access
IEEE Access
Computer Science