EPBLA: energy-efficient consolidation of virtual machines using learning automata in cloud data centers
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EPBLA: energy-efficient consolidation of virtual machines using learning automata in cloud data centers Nayereh Rasouli1
•
Ramin Razavi2 • Hamid Reza Faragardi3
Received: 11 May 2019 / Revised: 24 January 2020 / Accepted: 1 February 2020 Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract High demand for computational power by business, science, and applications has led to the creation of large-scale data centers that consume enormous amounts of energy. This high energy consumption not only imposes a significant operating cost but also has a negative impact on the environment (greenhouse gas emissions). A promising solution to reduce the amount of energy used by data centers is the consolidation of virtual machines (VMs) that allows some hosts to enter low consuming sleep modes. Dynamic migration (replacement) of VMs between physical hosts is an effective strategy to achieve VM consolidation. Dynamic migration not only saves energy by migrating the VMs hosted by idle hosts but can also avoid hotspots by migrating VMs from over-utilized hosts. In this paper, we presented a new approach, called extended-placement by learning automata (EPBLA), based on learning automata for dynamic replacement of VMs in data centers to reduce power consumption. EPBLA consists of two parts (i) a linear reward penalty scheme which is a finite action-set learning automata that runs on each host to make a fully distributed VM placement considering CPU utilization as a metric to categorize the hosts, and (ii) a continuous action-set learning automata as a policy for selecting an underload host initiating the migration process. A real-world workload is used to evaluate the proposed method. Simulation results showed the efficiency of EPBLA in terms of reduction of energy consumption by 20% and 30% compared with PBLA and Firefly, respectively. Keywords Energy consumption Learning automata Placement of virtual machines Cloud computing VM migration
1 Introduction Cloud computing is a new computing paradigm emerged in recent years. It is a model that enables ubiquitous, convenient and on-demand network access to a shared pool of & Nayereh Rasouli [email protected] Ramin Razavi [email protected] Hamid Reza Faragardi [email protected] 1
Department of Computer Engineering, Hashtgerd Branch, Islamic Azad University, Hashtgerd, Iran
2
School of Electrical and Computer Engineer, University of Tehran, Tehran, Iran
3
Department of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden
configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. In recent years, the IT infrastructure is rapidly growing due to the demand for computing power used by applications. In addition, modern data centers in cloud computing are hosting a variety of advanced applications. The high energy cost and greenhouse gas emissions are significant problems arising due to hig
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