Skip to main content
SpringerLink
Log in

Concluding Remarks

  • Chapter
  • First Online:
A Survey on Coordinated Power Management in Multi-Tenant Data Centers

  • 347 Accesses

Abstract

This chapter describes the open issues for future research and conclusions. Most of the survey research works made two assumptions. First, using the on-site “green” energy from renewables and energy storage devices (e.g., batteries) costs more than the “brown” energy from the grid. Second, the majority of the energy consumed by the data centers comes from the grid. These two assumptions are no longer true due to recent advances in technology and economy of scale. The future of coordinated power management lies in data center micro-grids where the data centers are both the energy suppliers and consumers.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ren, S. & Islam, M. A. (2014, June). Colocation demand response: Why do I turn off my servers? In 11th international conference on autonomic computing (pp. 201–208). Philadelphia, PA: USENIX Association. [Online]. Available: https://goo.gl/DT5tmP.

  2. Niu, L., Guo, Y., Li, H., & Pan, M. (2016, December). A nash bargaining approach to emergency demand response in colocation data centers. In 2016 IEEE global communications conference (GLOBECOM) (pp. 1–6). [Online]. Available: https://goo.gl/okffPu.

  3. Zhao, Z., Wu, F., Ren, S., Gao, X., Chen, G., & Cui, Y. (2016, August). Tech: A thermal-aware and cost efficient mechanism for colocation demand response. In 2016 45th international conference on parallel processing (ICPP) (pp. 464–473. [Online]. Available: https://goo.gl/OUepr1.

  4. Ahmed, K., Islam, M. A., & Ren, S. (2015). A contract design approach for colocation data center demand response. In IEEE/ACM international conference on computer-aided design, ser. ICCAD ’15 (pp. 635–640). Piscataway, NJ, USA: IEEE Press. [Online]. Available: http://goo.gl/0ZTul9.

  5. Tran, N., Do, C., Ren, S., Han, Z., & Hong, C. (2015, December). Incentive mechanisms for economic and emergency demand responses of colocation datacenters. IEEE Journal on Selected Areas in Communications, 33(12), 2892–2905. [Online]. Available: http://goo.gl/nmU1e8.

  6. Sun, Q., Ren, S., Wu, C., & Li, Z. (2016, June). An online incentive mechanism for emergency demand response in geo-distributed colocation data centers. In International conference on future energy systems, ser. e-Energy ’16 (pp. 3:1–3:13). New York, NY, USA: ACM. [Online]. Available: http://goo.gl/3PNA2Q.

  7. Gandhi, A., Harchol-Balter, M., Raghunathan, R., & Kozuch, M. A. (2012, November). AutoScale: Dynamic, robust capacity management for multi-tier data centers. ACM Transactions on Computer Systems, 30(4), 14:1–14:26. [Online]. Available: http://goo.gl/lxamQz.

  8. Qureshi, A., Weber, R., Balakrishnan, H., Guttag, J., & Maggs, B. (2009). Cutting the electric bill for internet-scale systems. In ACM SIGCOMM Conference on Data Communication, ser. SIGCOMM ’09 (pp. 123–134). New York, NY, USA: ACM. [Online]. Available: http://goo.gl/aV7dMs.

  9. Liu, Z., Lin, M., Wierman, A., Low, S. H., & Andrew, L. L. (2011). Greening geographical load balancing. In ACM SIGMETRICS joint international conference on measurement and modeling of computer systems, ser. SIGMETRICS ’11 (pp. 233–244). New York, NY, USA: ACM. [Online]. Available: http://goo.gl/DHgS7v.

  10. Urgaonkar, R., Urgaonkar, B., Neely, M. J., & Sivasubramaniam, A. (2011). Optimal power cost management using stored energy in data centers. In ACM SIGMETRICS joint international conference on measurement and modeling of computer systems, ser. SIGMETRICS ’11 (pp. 221–232). New York, NY, USA: ACM. [Online]. Available: http://goo.gl/HKg8vj.

  11. International Renewable Energy Agency. (2012, June). Renewable energy cost analysis – solar photovoltaics. Tech. Rep. [Online]. Available: http://goo.gl/NNNJCw.

  12. Muenzel, V., Mareels, I., de Hoog, J., Vishwanath, A., Kalyanaraman, S., & Gort, A. (2015, February). PV generation and demand mismatch: Evaluating the potential of Residential Storage. In Innovative smart grid technologies conference (ISGT), 2015 IEEE Power Energy Society (pp. 1–5). [Online]. Available: http://goo.gl/CymZ50.

  13. Islam, M., Ren, S., & Wang, X. (2014, November). GreenColo: A novel incentive mechanism for minimizing carbon footprint in colocation data center. In International green computing conference, (IGCC) (pp. 1–8). [Online]. Available: http://goo.gl/f9nr8F.

  14. Zhang, L., Li, Z., Wu, C., & Ren, S. (2015, December). Online electricity cost saving algorithms for co-location data centers. IEEE Journal on Selected Areas in Communications, 33(12), 2906–2919. [Online]. Available: http://goo.gl/45QUdf.

  15. Chen, N., Ren, X., Ren, S., & Wierman, A. (2015, September). Greening multi-tenant data center demand response. SIGMETRICS Performance Evaluation Review, 43(2), 36–38. [Online]. Available: http://goo.gl/HmcRnU.

  16. Zhang, L., Ren, S., Wu, C., & Li, Z. (2015, April). A truthful incentive mechanism for emergency demand response in colocation data centers. In IEEE INFOCOM, Hong Kong, China (pp. 2632–2640). [Online]. Available: http://goo.gl/9KqeBv.

  17. Mohsenian-Rad, A.-H., Wong, V., Jatskevich, J., Schober, R., & Leon-Garcia, A. (2010, December). Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Transactions on Smart Grid, 1(3), 320–331. [Online]. Available: http://goo.gl/rqjo6k.

  18. Guo, Y. & Pan, M. (2015, November). Coordinated energy management for colocation data centers in smart grids. In 2015 IEEE international conference on smart grid communications, (SmartGridComm) (pp. 840–845).

    Google Scholar 

  19. Wang, C., Nasiriani, N., Kesidis, G., Urgaonkar, B., Wang, Q., Chen, L. Y., et al. (2015). Recouping energy costs from cloud tenants: Tenant demand response aware pricing design. In ACM 6th international conference on future energy systems, ser. e-Energy ’15 (pp. 141–150). New York, NY, USA: ACM. [Online]. Available: https://goo.gl/x5dktv.

  20. Riekstin, A. C., James, S., Kansal, A., Liu, J., & Peterson, E. (2014, May). No more electrical infrastructure: Towards fuel cell powered data centers. SIGOPS Operating Systems Review, 48(1), 39–43. [Online]. Available: http://goo.gl/nb1IVG.

  21. Tu, J., Lu, L., Chen, M., & Sitaraman, R. K. (2013). Dynamic provisioning in next-generation data centers with on-site power production. In Proceedings of the fourth international conference on future energy systems, ser. e-Energy ’13 (pp. 137–148). New York, NY, USA: ACM. [Online]. Available: http://goo.gl/KynpDv.

  22. Wang, D., Ren, C., Sivasubramaniam, A., Urgaonkar, B., & Fathy, H. (2012, June). Energy storage in data centers: What, where, and how much? SIGMETRICS Performance Evaluation Review, 40(1), 187–198. [Online]. Available: http://goo.gl/ZsB5Tv.

  23. NASA. The impact of climate change on natural disasters. NASA Earth Observatory Website. [Online]. Available: https://goo.gl/78MZBx.

  24. Jones Lang Lasalle IP, Inc. (2016). North America Data Center Outlook - 2016. Tech. Rep. [Online]. Available: https://goo.gl/mn2O9y.

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science & Engineering, Kyung Hee University, Yongin, Gyeonggi, Korea (Republic of)

    Thant Zin Oo, Nguyen H. Tran & Choong Seon Hong

  2. Department of Electrical & Computer Engineering, University of California, Riverside, Riverside, CA, USA

    Shaolei Ren

Authors
  1. Thant Zin Oo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nguyen H. Tran
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shaolei Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Choong Seon Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Oo, T.Z., Tran, N.H., Ren, S., Hong, C.S. (2018). Concluding Remarks. In: A Survey on Coordinated Power Management in Multi-Tenant Data Centers. Springer, Cham. https://doi.org/10.1007/978-3-319-66062-2_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-66062-2_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66061-5

  • Online ISBN: 978-3-319-66062-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation