Managing Energy Consumption and Quality of Service in Data Centers

Marziyeh Bayati

2016

Abstract

The main goal of this paper is to manage the switching on/off of servers in a data center during time to adapt the system with incoming traffic changes to ensure a good performance and a reasonable energy consumption. In this work, the system is modeled by a queue then, an optimization algorithm is designed to manage energy consumption and quality of service in the data center. For several systems, the algorithm is tested by numerical analysis under various types of job arrivals: arrivals with constant rate, arrivals defined by an constant discrete distribution, arrivals specified by a variable discrete distribution over time, and arrivals modeled by discrete distributions obtained from real traffic traces. The optimization algorithm that we suggest, adapts and adjusts dynamically the number of operational servers according to: traffic variation, workload, cost of keeping a job in the buffer, cost of losing a job, and energetic cost for serving a job.

References

  1. Aidarov, K., Ezhilchelvan, P. D., and Mitrani, I. (2013). Energy-aware management of customer streams. Electr. Notes Theor. Comput. Sci., 296:199-210.
  2. Baliga, J., Ayre, R. W., Hinton, K., and Tucker, R. S. (2011). Green cloud computing: Balancing energy in processing, storage, and transport. Proceedings of the IEEE, 99(1):149-167.
  3. Bayati, M., Dahmoune, M., Fourneau, J., Pekergin, N., and Vekris, D. (2015). A tool based on traffic traces and stochastic monotonicity to analyze data centers and their energy consumption. In Valuetools 7815: 9th international conference on Performance evaluation methodologies and tools, page to appear. Acm.
  4. Berl, A., Gelenbe, E., Di Girolamo, M., Giuliani, G., De Meer, H., Dang, M. Q., and Pentikousis, K. (2010). Energy-Efficient Cloud Computing. The Computer Journal, 53(7):1045-1051.
  5. Chase, J. S., Anderson, D. C., Thakar, P. N., Vahdat, A. M., and Doyle, R. P. (2001). Managing energy and server resources in hosting centers. In ACM SIGOPS Operating Systems Review, volume 35, pages 103-116. ACM.
  6. Grunwald, D., Morrey, III, C. B., Levis, P., Neufeld, M., and Farkas, K. I. (2000). Policies for dynamic clock scheduling. In Proceedings of the 4th Conference on Symposium on Operating System Design & Implementation - Volume 4, OSDI'00, pages 6-6, Berkeley, CA, USA. USENIX Association.
  7. Koomey, J. (2011). Growth in data center electricity use 2005 to 2010. A report by Analytical Press, completed at the request of The New York Times, page 9.
  8. Lee, Y. C. and Zomaya, A. Y. (2012). Energy efficient utilization of resources in cloud computing systems. The Journal of Supercomputing, 60(2):268-280.
  9. Mazzucco, M. and Mitrani, I. (2012). Empirical evaluation of power saving policies for data centers. SIGMETRICS Performance Evaluation Review, 40(3):18-22.
  10. Mitrani, I. (2013). Managing performance and power consumption in a server farm. Annals OR, 202(1):121- 134.
  11. Patel, C. D., Bash, C. E., Sharma, R., and Beitelmal, M. (2003). Smart cooling of data centers. In Proceedings of IPACK.
  12. Reiss, C., Wilkes, J., and Hellerstein, J. L. (2011). Google cluster-usage traces: format + schema. Technical report, Google Inc., Mountain View, CA, USA. Revised 2012.03.20.
  13. Schwartz, C., Pries, R., and Tran-Gia, P. (2012). A queuing analysis of an energy-saving mechanism in data centers. In Information Networking (ICOIN), 2012 International Conference on, pages 70-75.
  14. Sericola, B. (1999). Availability analysis of repairable computer systems and stationarity detection. IEEE Trans. Computers, 48(11):1166-1172.
  15. Wilkes, J. (2011). More Google cluster data. Google research blog. Posted at http://googleresearch. blogspot.com/2011/11/more-google-clusterdata.html.
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Paper Citation


in Harvard Style

Bayati M. (2016). Managing Energy Consumption and Quality of Service in Data Centers . In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-184-7, pages 293-301. DOI: 10.5220/0005791802930301


in Bibtex Style

@conference{smartgreens16,
author={Marziyeh Bayati},
title={Managing Energy Consumption and Quality of Service in Data Centers},
booktitle={Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2016},
pages={293-301},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005791802930301},
isbn={978-989-758-184-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Managing Energy Consumption and Quality of Service in Data Centers
SN - 978-989-758-184-7
AU - Bayati M.
PY - 2016
SP - 293
EP - 301
DO - 10.5220/0005791802930301