Prediction-based underutilized and destination host selection approaches for energy-efficient dynamic VM consolidation i
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Prediction‑based underutilized and destination host selection approaches for energy‑efficient dynamic VM consolidation in data centers Kawsar Haghshenas1 · Siamak Mohammadi1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Improving the energy efficiency while guaranteeing quality of services (QoS) is one of the main challenges of efficient resource management of large-scale data centers. Dynamic virtual machine (VM) consolidation is a promising approach that aims to reduce the energy consumption by reallocating VMs to hosts dynamically. Previous works mostly have considered only the current utilization of resources in the dynamic VM consolidation procedure, which imposes unnecessary migrations and host power mode transitions. Moreover, they select the destinations of VM migrations with conservative approaches to keep the service-level agreements , which is not in line with packing VMs on fewer physical hosts. In this paper, we propose a regression-based approach that predicts the resource utilization of the VMs and hosts based on their historical data and uses the predictions in different problems of the whole process. Predicting future utilization provides the opportunity of selecting the host with higher utilization for the destination of a VM migration, which leads to a better VMs placement from the viewpoint of VM consolidation. Results show that our proposed approach reduces the energy consumption of the modeled data center by up to 38% compared to other works in the area, guaranteeing the same QoS. Moreover, the results show a better scalability than all other approaches. Our proposed approach improves the energy efficiency even for the largest simulated benchmarks and takes less than 5% time overhead to execute for a data center with 7600 physical hosts. Keywords Linear regression · VM consolidation · VM migration · Energy efficiency · Cloud data centers
* Siamak Mohammadi [email protected] Kawsar Haghshenas [email protected] 1
School of Electrical and Computer Engineering, University of Tehran, Tehran 17469‑37181, Iran
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K. Haghshenas, S. Mohammadi
1 Introduction High energy consumption has become one of the critical issues for today’s data centers. High operational cost and environmental effects are two main consequences of this usage. According to Koomey’s report [1], estimated annual electricity cost in large data centers is about 41% of the data center’s total operating costs. However, according to Shehabi’s latest report [2], a potential of 45% reduction in electricity usage can be achieved in new generation of sustainable and energy-efficient data centers by new resource management approaches. Virtualization technology in modern data centers [3] provides the opportunity of consolidating virtual machines (VM) of the data center dynamically. Dynamic VM consolidation techniques utilize live VM migration to pack as many VMs as possible on one physical host and switch idle hosts to low-power modes to decrease hosts’ energy consumption [4].
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