Task scheduling, resource provisioning, and load balancing on scientific workflows using parallel SARSA reinforcement learning agents and genetic algorithm
- 6 July 2020
- journal article
- research article
- Published by Springer Nature in The Journal of Supercomputing
- Vol. 77 (3) , 2800-2828
Abstract
No abstract availableKeywords
This publication has 55 references indexed in Scilit:
- Multi-objective workflow scheduling in Amazon EC2Cluster Computing, 2013
- URL: A unified reinforcement learning approach for autonomic cloud managementJournal of Parallel and Distributed Computing, 2012
- CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithmsSoftware: Practice and Experience, 2010
- Multi-heuristic dynamic task allocation using genetic algorithms in a heterogeneous distributed systemJournal of Parallel and Distributed Computing, 2010
- Cloud computing: state-of-the-art and research challengesJournal of Internet Services and Applications, 2010
- Scientific Workflow: A Survey and Research Directions2008
- Multi-objective optimization using genetic algorithms: A tutorialReliability Engineering & System Safety, 2006
- Resource Allocation in the Grid with Learning AgentsJournal of Grid Computing, 2005
- Critical path identification in the context of a workflowInformation and Software Technology, 2002
- Learning to act using real-time dynamic programmingArtificial Intelligence, 1995