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Modelling energy consumption of network transfers and virtual machine migration

De Maio, V, Prodan, R, Benedict, S and Kecskemeti, G (2015) Modelling energy consumption of network transfers and virtual machine migration. Future Generation Computer Systems, 56. pp. 388-406. ISSN 0167-739X

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Reducing energy consumption has become a key issue for data centres, not only because of economical benefits but also for environmental and marketing reasons. Therefore, assessing their energy consumption requires precise models. In the past years, many models targeting different hardware components, such as CPU, storage and network interface cards (NIC) have been proposed. However, most of them neglect energy consumption related to VM migration. Since VM migration is a network-intensive process, to accurately model its energy consumption we also need energy models for network transfers, comprising their complete software stacks with different energy characteristics. In this work, we present a comparative analysis of the energy consumption of the software stack of two of today's most used NICs in data centres, Ethernet and Infiniband. We carefully design for this purpose a set of benchmark experiments to assess the impact of different traffic patterns and interface settings on energy consumption. Using our benchmark results, we derive an energy consumption model for network transfers. Based on this model, we propose an energy consumption model for VM migration providing accurate predictions for paravirtualised VMs running on homogeneous hosts. We present a comprehensive analysis of our model on different machine sets and compare it with other models for energy consumption of VM migration, showing an improvement of up to 24% in accuracy, according to the NRMSE error metric. © 2015 Elsevier B.V.

Item Type: Article
Uncontrolled Keywords: 0805 Distributed Computing, 0806 Information Systems
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Publisher: Elsevier
Date Deposited: 02 Aug 2016 10:36
Last Modified: 04 Sep 2021 12:39
DOI or ID number: 10.1016/j.future.2015.07.007
URI: https://researchonline.ljmu.ac.uk/id/eprint/3971
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