Energy and quality of service-aware virtual machine consolidation in a cloud data center
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Energy and quality of service‑aware virtual machine consolidation in a cloud data center Anurina Tarafdar1 · Mukta Debnath1 · Sunirmal Khatua1 · Rajib K. Das1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The large-scale virtualized Cloud data centers consume huge amount of electrical energy leading to high operational costs and emission of greenhouse gases. Virtual machine (VM) consolidation has been found to be a promising approach to improve resource utilization and reduce energy consumption of the data center. However, aggressive consolidation of VMs tends to increase the number of VM migrations and leads to over-utilization of hosts. This in turn affects the quality of service (QoS) of the applications running in the VMs. Thus, reduction in energy consumption and at the same time ensuring proper QoS to the Cloud users are one of the major challenges among the researchers. In this paper, we have proposed an energy efficient and QoS-aware VM consolidation technique in order to address this problem. We have used Markov chain-based prediction approach to identify the over-utilized and under-utilized hosts in the data center. We have also proposed an efficient VM selection and placement policy based on linear weighted sum approach to migrate the VMs from over-utilized and under-utilized hosts considering both energy and QoS. Extensive simulations using real-world traces and comparison with state-of-art strategies show that our VM consolidation approach substantially reduces energy consumption within a data center while delivering suitable QoS. Keywords Cloud computing · Energy · Quality of service · Virtual machine consolidation · Virtual machine placement · Virtual machine selection
* Sunirmal Khatua [email protected] Anurina Tarafdar [email protected] Mukta Debnath [email protected] Rajib K. Das [email protected] 1
Department of Computer Science and Engineering, University of Calcutta, Kolkata, India
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1 Introduction Cloud computing enables dynamic and on-demand provisioning of infrastructure, platform and software as services in a pay-per-use manner. These are termed as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS), respectively [1]. Instead of bearing the huge cost needed to build and maintain their own infrastructure, many large and small enterprises outsource their computational requirements to the Cloud. Cloud service providers (CSPs), namely Google, Amazon, etc., have deployed large-scale virtualized data centers across the world in order to deliver services to their customers. These data centers containing numerous physical machines (hosts or servers) are responsible for consumption of enormous amount of electrical energy and emission of greenhouse gases. It has been reported that in 2016, the global data centers consumed around 416.2 terawatt hours of electricity which accounted for about 3% of the global electricity supply and 2% of the t
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