Babkin O.V., Varlamov A.А., Gorshunov R.А., Dos E.V., Kropachev A.V., Zuev D.О.
Babkin Oleg Vyacheslavovich - Strategy Consultant,
IBM;
Varlamov Aleksandr Aleksandrovich - CTO,
SHARXDC LLC,
MOSCOW;
Gorshunov Roman Aleksandrovich - Solution Architect,
AT&T, BRATISLAVA, SLOVAKIA;
Dos Evgenii Vladimirovich - Lead DevOps Architect,
EPAM, MINSK, REPUBLIC OF BELARUS;
Kropachev Artemii Vasilyevich - Principal Architect,
LI9 TECHNOLOGY SOLUTIONS, NORTH CAROLINA;
Zuev Denis Olegovich - Independent Consultant,
NEW JERSEY,
USA
Abstract: рower management for server clusters physical resources was analyzed. It was shown that low performance of data center infrastructure work refers to disproportion of servers’ utilization. Overconsumption problem could be solved by minimization of the active servers’ number within the bounds of the server consolidation procedure. In order to provide server consolidation implementation it is necessary to maintain acceptable performance level of the servers room infrastructure work. Server consolidation may cause performance degradation due to the conflict of using shared resources by virtual machines. It was demonstrated that threshold level of utilization regime analysis should be based in order to get a compromise between stable work of data center and opportunity for power savings which is associated with skipping of rare cases of servers’ peak load. Basic scheme of clustering-based correlation-aware virtualization includes trace data center servers’ physical resources utilization level, transformфation of utilization traces into binary sequence up to the utilization threshold value, clustering of virtual machines up to the binary sequence in order to maintain not overlapping of different clusters and virtual machines allocation at physical servers in order to minimize the possibility of the service performance degradation at peak period. It was develop power management procedure which consists from user-interactive and fast changing service, maintaining of the minimal performance degradation caused by physical resources sharing conflict and high correlation level of virtual machines. Thereby it is important to estimate proper measure to quantify the correlation coefficient between virtual machines to overcome the inefficiency of the conventional correlation metric. Pearson’s correlation coefficient was proved to be optimal instrument of the correlation of used data center virtual machines physical resources utilization quantifying. Developed model allows storing all samples and evenly distributing computational utilization as well as correlation between the events in the bounds of certain time period.
Keywords: data center, power consumption, virtual machine, clustering, Pearson’s correlation coefficient, performance degradation, peak load.
References
- Geng H., Data center handbook. Hoboken, NJ: John Wiley & Sons. Energy Star Program. “EDA Report to Congress on Server and Data Center Energy Efficiency”, 2007.
- Barroso L.A. and Holzle U. “The datacenter as a computer: An introduction to the design of warehouse-scale machines” Synthesis Lectures on Computer Architecture4. № 1, 2009: 1–108.
- Ferdman М., Adileh А., Kocberber О., Volos S., Alisafaee М., Jevdjic D., Kaynak С., Popescu A.D., Ailamaki А. and Falsafi В. “Clearing the clouds: a study of emerging scale-out workloads on modern hardware,” in ACM SIGARCH Computer Architecture News. Vol. 40. № 1. Р 37–48. ACM, 2012.
- Harris M., Data Center Infrastructure Management. Data Center Handbook, 601-618. doi:10.1002/9781118937563.ch33.
- Meisner D., Sadler С.М., Barroso L.A., Weber W.-D. and Wenisch T.F. “Power management of online data-intensive services,” in Computer Architecture (ISCA), 2011. 38th Annual International Symposium on, pp. 319–330. IEEE, 2011.
- Bobroff N. et al. “Dynamic placement of virtual machines for managing sla violations,” in Proc. IM2007.
- Jaramillo D., Furht B. & Agarwal A., Mobile Virtualization Technologies. Virtualization Techniques for Mobile Systems, 5-20. doi:10.1007/978-3-319-05741-5_2.
- Tickoo R. Iyer, R. Illikkal and Newell D. “Modeling virtual machine performance: challenges and approaches,” in ACM SIGMETRICS Performance Evaluation Review 37, 2010.
- Govindan S., Liu J., Kansal А. and Sivasubramaniam А. “Cuanta: quantifying effects of shared on-chip resource interference for consolidated virtual machines,” in Proceedings of the 2nd ACM Symposium on Cloud Computing. Р. 22. ACM, 2011.
- Wang L. & Lu Y., Power-efficient workload distribution for virtualized server clusters. 2010 International Conference on High Performance Computing. doi: 10.1109/hipc.2010.5713178.
- Meng Х. et al. “Efficient resource provisioning in compute clouds via VM multiplexign,” in Proc. ICAC, 2010.
- Chen М. et al. “Effective VM sizing in virtualized data centers,” inProc. IM, 2011.
- Halder К. et al. “Risk aware provisioning and resource aggregation based consolidation of virtual machines,” inProc. Cloud, 2012.
- Santos J.R., Turner Y. Virtual Machine Management, 2011. Mastering. 255-326. doi:10.1002/9781118257432.ch7.
- Kim J., Ruggiero М., Atienza D. and Lederberger М. “Correlation-aware virtual machine allocation for energy-efficient datacenters,” in Proc.Conference on Design, automation and Test in Europe (DATE). Р 1345–1350, 2013. № 5 (2003): 164–177.
- Khan S.U., Handbook on data centers. Place of publication not identified: Springer.
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Ссылка для цитирования. Babkin O.V., Varlamov A.А., Gorshunov R.А., Dos E.V., Kropachev A.V., Zuev D.О. POWER MANAGEMENT FOR SERVER CLUSTERS HARDWARE // VIII Международная научно-практическая конференция «Современные инновации: теория и практика развития современного научного знания» (Россия. Москва. 11 октября 2018). С. {см. сборник}.
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