Flexible Peak Shaving in Data Center by Suppression of Application Resource Usage

Masaki Samejima, Ha Tuan Minh, Norihisa Komoda

Abstract

We address the peak shaving of the electricity consumption in the data center. The conventional peak shaving method is “power capping” that limits the electricity consumption by all the applications in the server. In order to shave the peak of only the unimportant applications, we propose the flexible peak shaving by suppression of application resource usage. By monitoring the resource usage of all the applications, the proposed method decides how much the electricity consumption should be decreased with multiple regression analysis on the linear model between the electricity consumption and the CPU usage. As preliminary investigation, we constructed the linear model with using the observed values of the power consumption and CPU usage on the actual servers.

References

  1. Albadi, M. H., El-Saadany, E. F., 2008. A summary of demand response in electricity markets, Electric Power Systems Research, Vol.78, No.11, pp.1989- 1996.
  2. Almoosa, N., Song, W., Wardi, Y., Yalamanchili, S., 2012. A Power Capping Controller for Multicore Processors, American Control Conference (ACC), pp.4709-4714.
  3. Beloglazov, A., Buyya, R., 2010. Energy Efficient Resource Management in Virtualized Cloud Data Centers, Proc. of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGRID 7810), pp.826-831.
  4. Chen, Q., Grosso, P., van der Veldt, K., de Laat, C., Hofman, R., Bal, H., 2011. Profiling Energy Consumption of VMs for Green Cloud Computing, Proc. of 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing(DASC), pp.768-775.
  5. CPUlimit, 2012, http://cpulimit.sourceforge.net/.
  6. Elnozahy, E.N., Kistler, M., Rajamony, R., 2003. EnergyEfficient Server Clusters, Power-Aware Computer Systems, Lecture Notes in Computer Science, Vol. 2325, pp. 179-197.
  7. Jaiantilal, A., Jiang, Y., Mishra, S., 2010. Modeling CPU energy consumption for energy efficient scheduling, Proc. of the 1st Workshop on Green Computing (GCM 7810), pp.10-15.
  8. Kansal, A., Zhao, F., Liu, J., Kothari, N., Bhattacharya, A.A., 2010. Virtual machine power metering and provisioning, Proc. of the 1st ACM symposium on Cloud computing (SoCC 7810), pp.39-50.
  9. Kontorinis, V., Zhang, L.E., Aksanli, B., Sampson, J., Homayoun, H., Pettis, E., Tullsen, D.M., Rosing, T.S., 2012. Managing distributed UPS energy for effective power capping in data centers, 2012 39th Annual International Symposium on Computer Architecture (ISCA), 2012, pp.488-499.
  10. Palasamudram, D. S., Sitaraman, R. K., Urgaonkar, B., Urgaonkar, R., 2012. Using batteries to reduce the power costs of internet-scale distributed networks, Proc. of the Third ACM Symposium on Cloud Computing (SoCC 7812), No.11, pp.1-14.
  11. Pallis, G., 2010. Cloud Computing: The New Frontier of Internet Computing, IEEE Internet Computing, Vol. 14, No. 5, pp.70-73.
  12. Panda, P.R, Silpa, B.V.N., Shrivastava, A., Gummidipudi, K., 2010. Power-efficient System Design, Springer.
  13. Schulz, G., 2009. The Green and Virtual Data Center, Auerbach.
  14. Tsirogiannis, D., Harizopoulos, S., Shah, M.A., 2010. Analyzing the energy efficiency of a database server, Proc. of the 2010 ACM SIGMOD International Conference on Management of data (SIGMOD 7810), pp. 231-242.
  15. Wang, D., Ren C., Sivasubramaniam, A., Urgaonkar, B., Fathy, H., 2012. Energy storage in datacenters: what, where, and how much?, Proc. of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems (SIGMETRICS 7812). pp.187-198.
  16. Zomaya, A. Y., Lee, Y. C., 2012. Energy Efficient Distributed Computing Systems, John Wiley & Sons.
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Paper Citation


in Harvard Style

Samejima M., Tuan Minh H. and Komoda N. (2014). Flexible Peak Shaving in Data Center by Suppression of Application Resource Usage . In Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-028-4, pages 355-360. DOI: 10.5220/0004939503550360


in Bibtex Style

@conference{iceis14,
author={Masaki Samejima and Ha Tuan Minh and Norihisa Komoda},
title={Flexible Peak Shaving in Data Center by Suppression of Application Resource Usage},
booktitle={Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2014},
pages={355-360},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004939503550360},
isbn={978-989-758-028-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Flexible Peak Shaving in Data Center by Suppression of Application Resource Usage
SN - 978-989-758-028-4
AU - Samejima M.
AU - Tuan Minh H.
AU - Komoda N.
PY - 2014
SP - 355
EP - 360
DO - 10.5220/0004939503550360