Task Offloading and Resource Allocation Method for Edge Computing in Intelligent Coal Mining

Abstract

In the mining industry, the intelligentization of coal mining is the future development trend. However, the traditional centralized Internet of Things network model struggles to meet the interaction demands of intelligent devices in the context of intelligent coal mining. To address the the problem, we study the optimization strategies for underground edge computing based on the 6G network’s distributed architecture. We construct an intelligent coal mining edge computing architecture, considering the revenue maximization problem for multi-tasking with different requirements in underground scenarios. Finally, we propose a Joint Task Offloading and Resource Allocation for Revenue Maximization algorithm. Simulation experiments verify the advantages of our algorithm, including fast convergence speed and high system revenue.