A Survey on Energy-Aware Task Scheduling Approaches for Cyber-Physical Systems using Machine Learning

This paper presents a survey of energy-aware task scheduling in Cyber-Physical Systems (CPSs) using Machine Learning approaches. It discusses the challenges of energy-aware scheduling in CPSs, outlining the important considerations when designing scheduling algorithms. It reviews the existing literature on energy-aware CPS scheduling and provides an overview of the proposed machine learning-based approaches. Additionally, it identifies promising research directions and provides insights into the use of machine learning for energy-aware CPS scheduling.