Game-Theoretic Resource Allocation for Fog-Based Industrial Internet of Things Environment
Yingmo Jie, Cheng Guo, Kim‐Kwang Raymond Choo, Charles Zhechao Liu, Mingchu Li
Abstract
The significant volume, variety, and velocity of data received from the many Industrial Internet of Things (IIoT) devices and other systems in a cloud-based or fog-based environment can complicate an organization's effort in ensuring high quality of experience for data users (DUs). For example, how do we efficiently and fairly allocate resources among cloud centers (CCs), fog service providers (FSPs), and DUs? This is particularly crucial for the IIoT environment, such as those in critical infrastructure sectors, such as energy and dams. Therefore, in this article, we propose an optimal resource allocation scheme for a fog-based IIoT environment. Specifically, we introduce fog nodes (or FSPs) that compete with each other to provide services for the DUs using resources from the CC. To maximize resource utilization, we model the resource allocation problem as a double-stage Stackelberg game and propose three algorithms to achieve Nash equilibrium and Stackelberg equilibrium. Then, we evaluate the performance of our proposed scheme with and without having FSPs, as well as with another competing scheme. The findings demonstrate the importance of fog computing in resource allocation, and the performance of our scheme outperforms that of the other scheme.