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Sam Jabbehdari
North Tehran Branch, Islamic Azad University
Computer Science & IT Electrical & Electronics Engineering

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An Effiecient Approach for Resource Auto-Scaling in Cloud Environments Bahar Asgari; Mostafa Ghobaei Arani; Sam Jabbehdari
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 5: October 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (924.639 KB) | DOI: 10.11591/ijece.v6i5.pp2415-2424

Abstract

Cloud services have become more popular among users these days. Automatic resource provisioning for cloud services is one of the important challenges in cloud environments. In the cloud computing environment, resource providers shall offer required resources to users automatically without any limitations. It means whenever a user needs more resources, the required resources should be dedicated to the users without any problems. On the other hand, if resources are more than user’s needs extra resources should be turn off temporarily and turn back on whenever they needed. In this paper, we propose an automatic resource provisioning approach based on reinforcement learning for auto-scaling resources according to Markov Decision Process (MDP). Simulation Results show that the rate of Service Level Agreement (SLA) violation and stability that the proposed approach better performance compared to the similar approaches.
Co-Authors Bahar Asgari Mostafa Ghobaei Arani