Reinforcement Learning in Process Scheduling

An efficient scheduling algorithm for a CPU has always been on the lookout by researchers and engineers since the invention of computers. Today most of the tasks are running online facilitated by servers. So, the requirement for fast, efficient, and reliable scheduling algorithms is the need of the hour. However, the traditional heuristic algorithms are having issues like complexity and uncertainty, so it is important to apply innovative technology to improve the task scheduling to ensure the efficient performance of these heavyduty systems. This study aims at developing a new scheduling model that integrates both optimized task scheduling and resource utilization using deep reinforcement learning algorithms.