Minimizing Environmental Footprints of Data Centers under Budget and Service Requirement Constraints

Waqaas Munawar, Jian-Jia Chen, Minming Li

2014

Abstract

The energy consumption of data centers (DCs) has been increasing, which will continue due to the increase of Internet traffic and stringent service level agreements (SLAs). Analogously, the protection of global and local environments has also driven the regulation authorities to encourage energy consumers, especially corporate entities, for the usage of green energy sources. However, the green energy is usually more expensive (up to four to five times for some cases) than the traditional energy generated from coal and petroleum. One essential problem for managing DCs, according to the greenness tendency, is to minimize the environmental penalty (or equivalently to maximize the greenness) by dispatching the requests to proper DCs under the SLA and budget constraints. This paper presents optimization techniques for dynamic workload balancing for cloud-scale data center (DC) management. We present a model for commonly found electricity tariffs for green energy and provide an efficient heuristic algorithm to maximize its usage while incorporating its intermittent availability. We evaluate the presented solution with real-life traces of electricity prices and DC workloads. Extensive evaluations support our solution’s potential to minimize the environmental penalty for Internet service providers under the budget while fulfilling their SLAs.

References

  1. Apple Inc. (2012). Apple facilities environmental report. http://images.apple.com/environment/ reports/docs/Apple Facilities Report 2012.pdf.
  2. Box, J. and Jenkins, G. (1994). Reinsel. Time Series Analysis, Forecasting and Control.
  3. Chase, J. et al. (2001). Managing energy and server resources in hosting centers. In ACM SIGOPS Operating Systems Review.
  4. Chen, J.-J. et al. (2011). Power management schemes for heterogeneous clusters under quality of service requirements. In SAC.
  5. Commission, E. (2013). The EU emissions trading system (EU ETS) - policies - climate action.
  6. Cortez, P., Rio, M., Rocha, M., and Sousa, P. (2006). Internet traffic forecasting using neural networks. In IJCNN'06. IEEE.
  7. Google (2011). Google's Green PPAs: What, How, and Why - R 02. Google White Papers.
  8. Guerra, R. et al. (2008). Attaining soft real-time constraint and energy-efficiency in web servers. In SAC.
  9. Heo, J., Henriksson, D., Liu, X., and Abdelzaher, T. (2007). Integrating adaptive components: An emerging challenge in performance-adaptive systems and a server farm case-study. In RTSS, pages 227-238. IEEE.
  10. Johnson, D. and Garey, M. (1979). Computers and intractability: A guide to the theory of np-completeness. Freeman&Co, San Francisco.
  11. Le, K., Bianchini, R., Martonosi, M., and Nguyen, T. (2009). Cost-and energy-aware load distribution across data centers. HotPower.
  12. Le, K. et al. (2010a). Capping the brown energy consumption of internet services at low cost. In Green Computing Conference. IEEE.
  13. Le, K. et al. (2010b). Managing the cost, energy consumption, and carbon footprint of internet services. In ACM SIGMETRICS.
  14. Li, J. et al. (2012). Towards optimal electric demand management for internet data centers. IEEE Transactions on Smart Grid.
  15. Luo, J. et al. (2013). Data center energy cost minimization: A spatio-temporal scheduling approach. In INFOCOM.
  16. Mathew, V. et al. (2012). Energy-aware load balancing in content delivery networks. In INFOCOM, pages 954 -962.
  17. NC-RETS (2013). North carolina renewable energy tracking system (NC-RETS). http://www.ncrets.org/.
  18. NYISO (2013). New York Independent System Operator. http://www.nyiso.com/.
  19. Paul Ontellini (2011). Intel CEO speaking at Dell World.
  20. Qureshi, A. et al. (2009). Cutting the electric bill for internet-scale systems. In ACM SIGCOMM, pages 123-134.
  21. Rao, L. et al. (2010). Minimizing electricity cost: Optimization of distributed internet data centers in a multielectricity-market environment. In INFOCOM, pages 1-9. IEEE.
  22. Shah, A. J. et al. (2008). Optimization of global data center thermal management workload for minimal environmental and economic burden. Components and Packaging Technologies, IEEE Transactions on, 31(1):39- 45.
  23. SolarBuzz (2013). Cost-Competitiveness-Solarbuzz. http://solarbuzz.com/facts-and-figures/marketsgrowth/cost-competitiveness.
  24. Stansberry, M. and Kudritzki, J. (2012). Data center industry survey. Technical report, Uptime Institute.
  25. Stewart, C. et al. (2009). Some joules are more precious than others: Managing renewable energy in the datacenter. In HotPower.
  26. Upson, S. (2007). The greening of google. Spectrum, IEEE, pages 24-28.
  27. Urdaneta, G. et al. (2009). Wikipedia workload analysis for decentralized hosting. Elsevier Comp. Networks.
  28. Verma, A. et al. (2010). Brownmap: Enforcing power budget in shared data centers. ACM Middleware, pages 42-63.
  29. Wang, S. et al. (2012). Power-saving design for server farms with response time percentile guarantees. In RTAS, pages 273-284.
  30. Webb, M. et al. (2008). Smart 2020: Enabling the low carbon economy in the information age. The Climate Group. London.
  31. You, C. and Chandra, K. (1999). Time series models for internet data traffic. In LCN'99. IEEE.
  32. Zhang, Y. et al. (2011). Greenware: Greening cloud-scale data centers to maximize the use of renewable energy. In Middleware.
  33. Zhang, Y., Wang, Y., and Wang, X. (2012). Electricity bill capping for cloud-scale data centers that impact the power markets. In ICPP.
  34. Zhao, W., Olshefski, D., and Schulzrinne, H. G. (2000). Internet quality of service: An overview.
Download


Paper Citation


in Harvard Style

Munawar W., Chen J. and Li M. (2014). Minimizing Environmental Footprints of Data Centers under Budget and Service Requirement Constraints . In Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-025-3, pages 222-232. DOI: 10.5220/0004934202220232


in Bibtex Style

@conference{smartgreens14,
author={Waqaas Munawar and Jian-Jia Chen and Minming Li},
title={Minimizing Environmental Footprints of Data Centers under Budget and Service Requirement Constraints},
booktitle={Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS,},
year={2014},
pages={222-232},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004934202220232},
isbn={978-989-758-025-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS,
TI - Minimizing Environmental Footprints of Data Centers under Budget and Service Requirement Constraints
SN - 978-989-758-025-3
AU - Munawar W.
AU - Chen J.
AU - Li M.
PY - 2014
SP - 222
EP - 232
DO - 10.5220/0004934202220232