Computation Resource Allocation and Task Assignment Optimization in Vehicular Fog Computing: A Contract-Matching Approach

TLDR

Vehicular fog computing offloads tasks from base stations to nearby vehicles, reducing processing delay, but faces challenges such as insufficient incentive and task assignment mechanisms. The study aims to minimize network delay by integrating contract‑matching approaches. An incentive mechanism based on contract theory tailored to vehicle types is proposed, and the task assignment problem is reformulated as a two‑sided matching problem solved by a pricing‑based stable‑matching algorithm that iteratively proposes and raises prices to reach stability. Numerical experiments demonstrate that the proposed scheme yields significant performance improvements.

Abstract

Vehicular fog computing (VFC) has emerged as a promising solution to relieve the overload on the base station and reduce the processing delay during the peak time. The computation tasks can be offloaded from the base station to vehicular fog nodes by leveraging the under-utilized computation resources of nearby vehicles. However, the wide-area deployment of VFC still confronts several critical challenges, such as the lack of efficient incentive and task assignment mechanisms. In this paper, we address the above challenges and provide a solution to minimize the network delay from a contract-matching integration perspective. First, we propose an efficient incentive mechanism based on contract theoretical modeling. The contract is tailored for the unique characteristic of each vehicle type to maximize the expected utility of the base station. Next, we transform the task assignment problem into a two-sided matching problem between vehicles and user equipment. The formulated problem is solved by a pricing-based stable matching algorithm, which iteratively carries out the "propose" and "price-rising" procedures to derive a stable matching based on the dynamically updated preference lists. Finally, numerical results demonstrate that significant performance improvement can be achieved by the proposed scheme.