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Minimization of Costs and Energy Consumption in a Data Center by a Workload-Based Capacity Management

Part of the Lecture Notes in Computer Science book series (LNCCN,volume 8945)


In this paper we present an approach to improve power and cooling capacity management in a data center by taking into account knowledge about applications and workloads. We apply power capping techniques and proper cooling infrastructure configuration to achieve savings in energy and costs. To estimate values of a total energy consumption and costs we simulate both IT software/hardware and cooling infrastructure at once using the CoolEmAll SVD Toolkit. We also investigated the use of power capping to adjust data center operation to variable power supply and pricing. By better adjusting cooling infrastructure to specific types of workloads, we were able to find a configuration which resulted in energy, OPEX and CAPEX savings in the range of 4–25 %.


  • Data centers
  • Energy efficiency
  • Simulations
  • Heat-aware
  • Metrics
  • OPEX

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  1. AICIA Grupo de Termotecnia de la Escuela Superior de Ingenieros Industriales de la Universidad de Sevilla. Calificación de Eficiencia Energética de Edificios. Condiciones de aceptación de procedimientos alternativos a LIDER y CALENER. Gobierno de España. Ministerio de vivienda. Ministerio de Industria, Turismo y Comercio. Instituto para la diversificación y ahorro de energía (2009)

    Google Scholar 

  2. The All4Green project website.

  3. Avelar, V., Azevedo, D., French, A.: The Green Grid. White paper # 49. PUE ™: A comprehensive examination of the metric (2012)

    Google Scholar 

  4. Chen, H., Hankendi, C., Caramanis, M.C., Coskun, A.K.: Dynamic server power capping for enabling data center participation in power markets. In: Proceedings of the International Conference on Computer-Aided Design, ICCAD 2013, pp. 122–129. IEEE Press, Piscataway (2013)

    Google Scholar 

  5. vor dem Berge, M., Da Costa, G., Kopecki, A., Oleksiak, A., Pierson, J.-M., Piontek, T., Volk, E., Wesner, S.: Modeling and simulation of data center energy-efficiency in CoolEmAll. In: Huusko, J., de Meer, H., Klingert, S., Somov, A. (eds.) E\(^2\)DC 2012. LNCS, vol. 7396, pp. 25–36. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  6. Da Costa, G., Hlavacs, H., Hummel, K., Pierson, J.-M.: Modeling the energy consumption of distributed applications. In: Ahmad, I., Ranka, S. (eds.) Handbook of Energy-Aware and Green Computing. Chapman & Hall, CRC Press, Baco Raton (2012)

    Google Scholar 

  7. Kemma, R., Park, D.: Methodology Study Eco-design of Energy-using Products MEEUP. Final report. VHK. Delft, The Netherlands (2005). Accessed 10 Jan 2014

  8. Kontorinis, V., Zhang, L.E., Aksanli, B., Sampson, J., Homayoun, H., Pettis, E., Tullsen, D.M., Simunic Rosing, T.: Managing distributed UPS energy for effective power capping in data centers. In: 2012 39th Annual International Symposium on Computer Architecture (ISCA), pp. 488–499, 9–13 June 2012. doi:10.1109/ISCA.2012.6237042

  9. Kurowski, K., Oleksiak, A., Piatek, W., Piontek, T., Przybyszewski, A., Weglarz, J.: DCworms - a tool for simulation of energy efficiency in distributed computing infrastructures. Simul. Model. Pract. Theory 39, 135–151 (2013). ISSN 1569–190X,

    CrossRef  Google Scholar 

  10. Hankendi, C., Reda, S., Coskun, A.K.: vCap: adaptive power capping for virtualized servers. In: 2013 IEEE International Symposium on Low Power Electronics and Design (ISLPED), pp. 415–420, 4–6 September 2013. doi:10.1109/ISLPED.2013.6629334

  11. Chetsa, G.L.T., Lefevre, L., Pierson, J.-M., Stolf, P., Da Costa, G.: DNA-inspired scheme for building the energy profile of HPC systems. In: Huusko, J., de Meer, H., Klingert, S., Somov, A. (eds.) E\(^2\)DC 2012. LNCS, vol. 7396, pp. 141–152. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  12. Lo, V., Mache, J., Windisch, K.: A comparative study of real workload traces and synthetic workload models for parallel job scheduling. In: Feitelson, D.G., Rudolph, L. (eds.) JSSPP 1998. LNCS, vol. 1459, pp. 25–46. Springer, Heidelberg (1998)

    CrossRef  Google Scholar 

  13. Rassmussen, N.: Determining Total Cost of ownership for data center and network room infrastructure. WP 6 APC. Schneider Electrics Data Center Science Center (2011)

    Google Scholar 

  14. Sisó, L., Forns, R.B., Napolitano, A., Salom, J., Da Costa, G., Volk, E., Donoghue, A.: D5.1 White paper on Energy- and Heat-aware metrics for computing modules - CoolEmAll Deliverable (2012).

  15. Sisó, L., Salom, J., Jarus, M., Oleksiak, A., Zilio, T.: Energy and heat-aware metrics for data centers: metrics analysis in the framework of CoolEmAll project. In: Third International Conference on Cloud and Green Computing (CGC), pp. 428–434 (2013)

    Google Scholar 

  16. Volk, E., Tenschert, A., Gienger, M., Oleksiak, A., Sisó, L., Salom, J.: Improving energy efficiency in data centers and federated cloud environments: comparison of CoolEmAll and Eco2Clouds approaches and metrics. In: Third International Conference on Cloud and Green Computing (CGC), pp. 443–450 (2013)

    Google Scholar 

  17. Liu, Z., Chen, Y., Bash, C., Wierman, A., Gmach, D., Wang, Z., Marwah, M., Hyser, C.: Renewable and cooling aware workload management for sustainable data centers. SIGMETRICS Perform. Eval. Rev. 40(1), 175–186 (2012)

    CrossRef  Google Scholar 

  18. Research: The economics of prefabricated modular datacenters (2012)

    Google Scholar 

  19. Feitelson, D.: Workload modeling for computer systems performance evaluation. Accessed 30 Dec 2012

  20. European Central Bank.

  21. Eurostat. European Commission. Accessed 06 March 2014

  22. ParallelWorkload Archive.

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The results presented in this paper are partially funded by the European Commission under contract 288701 through the project CoolEmAll and by a grant from Polish National Science Center under award number 2013/08/A/ST6/00296.

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Correspondence to Ariel Oleksiak .

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Da Costa, G., Oleksiak, A., Piatek, W., Salom, J., Sisó, L. (2015). Minimization of Costs and Energy Consumption in a Data Center by a Workload-Based Capacity Management. In: Klingert, S., Chinnici, M., Rey Porto, M. (eds) Energy Efficient Data Centers. E2DC 2014. Lecture Notes in Computer Science(), vol 8945. Springer, Cham.

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  • Print ISBN: 978-3-319-15785-6

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