Show simple item record

dc.contributor.authorHabib, Arafat
dc.contributor.authorKhan, Muhidulislam
dc.identifier.citationHabib, A., & Khan, M. I. (2016). Reinforcement learning based autonomic virtual machine management in clouds. Paper presented at the 2016 5th International Conference on Informatics, Electronics and Vision, ICIEV 2016, 1083-1088. 10.1109/ICIEV.2016.7760166en_US
dc.descriptionThis conference paper was published in the IEEE Xplore [ © 2016 IEEE] and the definite version is available at : The Journal's website is at:
dc.description.abstractCloud computing is a rapidly emerging field, services and applications are more or less 24/7. Resource dimensioning in this field is a great issue. Research is already going on to imply reinforcement learning to automate decision making process in case of addition, reduction, migration and maintenance of the Virtual Machines (VM) to balance the service level performance and VM management cost. Models have been proposed in this case based on Q-learning, a very popular reinforcement learning technique that is used to find optimal action selection policy for any finite Markov Decision Process (MDP). In this paper we propose to work with the challenges like proper initialization of the early stages, designing the states, actions, transitions using Markov Decision Process (MDP) and solving the MDP with two popular reinforcement learning techniques, Q-learning and SARSA(Λ).en_US
dc.publisher© 2016 IEEEen_US
dc.subjectCloud computingen_US
dc.subjectMarkov decision processen_US
dc.subjectReinforcement learningen_US
dc.subjectVirtual machinesen_US
dc.titleReinforcement learning based autonomic virtual machine management in cloudsen_US
dc.typeConference paperen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record