DRLBTSA: Deep reinforcement learning based task-scheduling algorithm in cloud computing

• Published in: Multimedia tools and applications Vol. 83; no. 3; pp. 8359 - 8387
• Main Authors: Mangalampalli, Sudheer, Karri, Ganesh Reddy, Kumar, Mohit, Khalaf, Osama Ibrahim, Romero, Carlos Andres Tavera, Sahib, GhaidaMuttashar Abdul
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2024; Springer Nature B.V
• Subjects: Algorithms; Cloud computing; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Deep learning; Energy consumption; Heterogeneity; Heuristic methods; Heuristic task scheduling; Machine learning; Multimedia; Multimedia Information Systems; Scheduling; Simulation; Special Purpose and Application-Based Systems; Workload; Workloads; Energy consumption; Cloud Computing; Deep Q- Learning; Task Scheduling; SLA violation; Makespan; Machine Learning

Task scheduling in cloud paradigm brought attention of all researchers as it is a challenging issue due to uncertainty, heterogeneity, and dynamic nature as they are varied in size, processing capacity and number of tasks to be scheduled. Therefore, ineffective scheduling technique may lead to incre...