A Reinforcement Learning Method forJoint Minimization of Energy Consumption and Delay in Fog Computing

Document Type : Original Research (Full Papers)

Authors

Department of Computer and Information Technology Engineering Qazvin Branch, Islamic Azad University

10.22094/jcr.2022.1963008.1274

Abstract

nowadays, there is a growing demand for the use of fog computing in applications such as e-health, agriculture, industry, and intelligent transportation management. In fog computing, optimal offloading is of crucial importance due to the limited energy of mobile devices. In this regard, using machine learning methods has recently attracted much attention. This paper presents a reinforcement learning-based approach to motivate users to offload their tasks. We propose a self-organizing algorithm for offloading based on Q-learning theory. Performance evaluation of the proposed method against traditional and state-of-the-art methods shows that it consumes less energy. It also reduces the execution time of tasks and results in less consumption of network resources.

Keywords


  • Receive Date: 11 July 2022
  • Revise Date: 10 October 2022
  • Accept Date: 27 October 2022
  • First Publish Date: 01 November 2022