Abstract The rapid growth in demand for getting various services combined with dynamic and diverse nature of requests initiated in cloud environments have led to the establishment of huge data centers which consume a vast amount of energy. On the other hand, in order to attract more users in dynamic business cloud environments, providers have to provide high quality of service for their customers based on defined Service Level Agreement (SLA) contracts. Hence, in order to maximize their revenue, resource providers need to minimize both energy consumptions and SLA violations simultaneously. This study proposes a new six-phase procedure for on-line resource management process. More precisely, this study proposes addition of two new phases to the default on-line resource management process including VM sorting phase and condition evaluation phase. Moreover, this paper shows the deficiencies of present resource management methods which fail to consider all effective system parameters as well as their importance, and do not have load prediction models. The results of simulations using cloudSim simulator validates the applicability of our proposed algorithms in reducing energy consumption as well as decreasing SLA violations and number of VMs' migration in cloud data centers.

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[22] Xiao Z., Song W., and Chen Q., Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment, IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 6, pp. 1107-1117, 2010. Ehsan Arianyan received the M.S. degree from Amirkabir University of Technology, Tehran, Iran, in 2010. He is currently working toward the Ph.D. degree with the Department of Electrical Engineering. He is the author of more than 10 peer-reviewed papers as well as 3 books related to cloud computing. His research interests include cloud computing, parallel computing, and decision algorithms. Hassan Taheri (M 90) received the M.S. and Ph.D. degrees from the University of Manchester, Manchester, U.K., in 1978 and 1988, respectively. He is currently an associate professor with the Department of Electrical Engineering, Amirkabir University of Technology. His research interests include cloud computing, teletraffic engineering, and quality of service in fixed and mobile communication networks. Saeed Sharifian received the M.S. and Ph.D. degrees from the Amirkabir University of Technology, Tehran, Iran, in 2002 and 2009, respectively. He is now an assistant professor with the Department of Electrical Engineering, Amirkabir University of Technology. His research interests include high-performance web server architecture, parallel computing and programming, sensor networks, as well as performance modeling and evaluation. Mohsen Tarighi received the M.S. and Ph.D. degrees from the Amirkabir University of Technology, Tehran, Iran, in 2008 and 2015, respectively. His research interests include cluster computing, virtualization, and decision algorithms.