Resource Management in Vehicular Fog Networks Based on Contract Theory

Haghighizadeh, R.; Zali, Z.

doi:10.47176/TMI.2025

Resource Management in Vehicular Fog Networks Based on Contract Theory

Document Type : Original Article

Authors

R. Haghighizadeh

Z. Zali

Department of Electrical Engineering, School of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran

10.47176/TMI.2025

Abstract

Fog computing is a distributed infrastructure that extends computing, communication, and storage capabilities toward the network edge. Compared to cloud computing, fog computing can support delay-sensitive service requests while reducing energy consumption and traffic congestion. Fog computing contributes to efficient resource utilization and improved performance in terms of latency, bandwidth, and energy consumption. However, one of the major challenges in fog computing is the limited computational capacity of fog nodes under increasing daily demand, especially during peak hours, which can lead to severe performance degradation. Therefore, an optimal mechanism is required to ensure satisfactory quality of service (QoS). Integrating fog computing with vehicular ad hoc networks, leading to vehicular fog computing (VFC), has emerged as a promising solution to reduce overload at base stations and minimize processing delays during peak periods. In this approach, the surplus computational resources of nearby vehicles are utilized as an on-demand, low-cost option. Consequently, the computing resources provided by a large group of vehicles can be aggregated to alleviate network congestion during peak hours without additional servers, enabling real-time computational scalability. Nevertheless, the large-scale deployment of vehicular fog networks still faces several critical challenges, such as the lack of efficient incentive mechanisms and task assignment strategies. In this study, we first propose a solution to minimize network delay from the perspective of integrated contract-based optimization. Next, the problem of computational task allocation is formulated as a two-sided matching problem between vehicles and users, and a stable, QoS-aware matching algorithm is introduced to solve it. Finally, task offloading decisions are performed to minimize total network latency. The proposed scheme can effectively guarantee network load balancing and improve the utilization of idle vehicular resources.

Keywords

Fog Computing

Task Allocation

Quality of Service

Vehicular Fog Computing