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RE-UPS: an adaptive distributed energy storage system for dynamically managing solar energy in green datacenters

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Abstract

Datacenters, the essential infrastructures for supercomputing and cloud computing, are facing increasing pressure of capping tremendous power consumption and carbon emission. Many studies have proposed to leverage energy storage devices to shave peak power or smooth intermittent power for datacenters, respectively. However, a joint energy management of peak shaving and renewable energy harvesting in datacenters is still lacking. In this paper, we propose a new power management scheme named RE-UPS, which explores the opportunity to shave datacenter peak power demand with renewable energy. RE-UPS is based on the emerging distributed energy storage architecture and existing UPS infrastructure of datacenter. It further leverages a dynamic heuristic algorithm to determine the appropriate energy storage allocation and server power sources. The proposed energy management policies can greatly optimize the design among maximizing renewable energy harvest, shaving peak power, and maintaining UPS energy availability. Compared to the baseline power management schemes, RE-UPS can averagely improve backup energy capacity by 28 %, extend battery lifetime by 42 %, increase green energy utilization by 78 %, and reduce workload performance degradation by 13 %.

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References

  1. Pahlavan A, Momtazpour M, Goudarzi M (2014) Power reduction in HPC data centers: a joint server placement and chassis consolidation approach. J Supercomput 70(2):845

    Article  Google Scholar 

  2. Kliazovich D, Bouvry P, Khan SU (2012) GreenCloud: a packet-level simulator of energy-aware cloud computing data centers. J Supercomput 62(3):1263

    Article  Google Scholar 

  3. Basmadjian R, De Meer H, Lent R, Giuliani G (2012) Cloud computing and its interest in saving energy: the use case of a private cloud. J Cloud Comput 1(1):1

    Article  Google Scholar 

  4. Global datacenter power demand. http://www.computerweekly.com/news/2240164589/Datacentre-power-demand-gr

  5. Barroso LA, Hölzle U (2009) The datacenter as a computer: an introduction to the design of warehouse-scale machines. Synth Lect Comput Archit 4(1):1

    Article  Google Scholar 

  6. Liu L, Li C, Sun H, Hu Y, Li T, Xin J, Zheng N (2015) HEB: deploying and managing hybrid energy buffers for improving datacenter efficiency and economy. In: International symposium on computer architecture (ISCA), ACM

  7. Govindan S, Sivasubramaniam A, Urgaonkar B (2011) Benefits and limitations of tapping into stored energy for datacenters. In: International symposium on computer architecture (ISCA), IEEE

  8. Liu L, Li C, Sun H, Hu Y, Li T (2015) BAAT: towards dynamically managing battery aging in green datacenters. In: IEEE/IFIP International conference on dependable systems and networks (DSN), IEEE/IFIP

  9. Govindan S, Wang D, Sivasubramaniam A, Urgaonkar B (2012) Leveraging stored energy for handling power emergencies in aggressively provisioned datacenters. In: International conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), ACM

  10. Li C, Hu Y, Zhou R, Liu M, Liu L, Yuan J, Li T (2013) Enabling datacenter servers to scale out economically and sustainably. In: International symposium on microarchitecture (MICRO), ACM

  11. Goiri Í, Katsak W, Le K, Nguyen TD, Bianchini R (2013) Parasol and GreenSwitch: managing datacenters powered by renewable energy. In: International conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), ACM

  12. Goiri Í, Le K, Nguyen TD, Guitart J, Torres J, Bianchini R (2012) GreenHadoop: leveraging green energy in data-processing frameworks. In: Proceedings of the 7th ACM European conference on computer systems, ACM

  13. Li C, Qouneh A, Li T (2012) iSwitch: coordinating and optimizing renewable energy powered server clusters. In: International symposium on computer architecture (ISCA), IEEE

  14. Liu L, Li C, Sun H, Hu Y, Xin J, Zheng N, Li T (2015) Leveraging Heterogeneous Power for Improving Datacenter Efficiency and Resiliency. IEEE Comput Archit Lett 14(1):41

  15. Liu L, Sun H, Hu Y, Xin J, Zheng N, Tao L (2014) Leveraging distributed UPS energy for managing solar energy powered data centers. In: International green computing conference (IGCC), IEEE

  16. Karve S (2002) Three of a kind [UPS topologies, IEC standard]. IEE Rev 46(2):27

    Article  Google Scholar 

  17. Govindan S, Wang D, Chen L, Sivasubramaniam A, Urgaonkar B (2011) Towards realizing a low cost and highly available datacenter power infrastructure. In: Proceedings of the 4th workshop on power-aware computing and systems, ACM

  18. Box GE, Jenkins GM, Reinsel GC (2003) Time series analysis: forecasting and control. IEEE Trans Autom Control 17(2):281

    Google Scholar 

  19. Outback power inc. http://www.outbackpower.com/outback-products/integrated-systems

  20. Logs of real parallel workloads from production systems. http://www.cs.huji.ac.il/labs/parallel/workload/logs.html

  21. The internet traffic archive. http://ita.ee.lbl.gov/

  22. Jongerden MR, Haverkort BR (2009) Which battery model to use? Softw IET 3(6):445

    Article  Google Scholar 

  23. Homer energy. http://www.homerenergy.com/index.html

  24. Specpower\_ssj2008. http://www.spec.org/power-ssj2008/

  25. Unit conversions, emissions factors, and other reference data. http://www.epa.gov/

  26. Xu Z, Mie L, Liu Y, Hu C, Chen L (2014) Semantic enhanced cloud environment for surveillance data management using video structural description. Comput 85(20):1

    Google Scholar 

  27. Hu C, Xu Z, Liu Y, Mei L, Chen L, Luo X (2014) Semantic link network-based model for organizing multimedia big data. Emerg Top Comput IEEE Trans 2(11):376

    Article  Google Scholar 

  28. Xu Z, Liu Y, Mei L, Hu C, Chen L (2015) Evaluation of numerical weather prediction for intraday solar forecasting in the continental United States. J Syst Softw 102(8):217

    Article  Google Scholar 

  29. Ferdaus MH, Murshed M (2014) Energy-aware virtual machine consolidation in IaaS cloud computing. Cloud Comput 201(4):179

    Google Scholar 

  30. Singh R, Irwin DE, Shenoy PJ, Ramakrishnan KK (2013) Yank: enabling green data centers to pull the plug. In: Symposium on networked systems design and implementation (NSDI), USENIX

  31. Li C, Hu Y, Longjun L, Juncheng G, Song M, Liang X, Yuan J, Li T (2015) Towards sustainable in-situ server systems in the big data era. In: International symposium on computer architecture (ISCA), ACM

  32. Cavallaro C, Musumeci S, Santonocito C, Pappalardo M (2009) Smart photovoltaic UPS system for domestic appliances. In: International conference on clean electrical power (ICCEP), IEEE

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Acknowledgments

This work was supported in part by NSF Grants 1423090, 1117261, 61128004, by NSFC Grant 61274028.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Xi’an Jiaotong University, Xi’an, China

    Longjun Liu, Hongbin Sun, Jingmin Xin & Nanning Zheng

  2. Department of Computer Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China

    Chao Li

  3. Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA

    Yang Hu & Tao Li

Authors
  1. Longjun Liu
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  2. Hongbin Sun
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  3. Chao Li
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  4. Yang Hu
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  5. Jingmin Xin
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  6. Nanning Zheng
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  7. Tao Li
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Correspondence to Hongbin Sun.

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Liu, L., Sun, H., Li, C. et al. RE-UPS: an adaptive distributed energy storage system for dynamically managing solar energy in green datacenters. J Supercomput 72, 295–316 (2016). https://doi.org/10.1007/s11227-015-1529-2

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  • DOI: https://doi.org/10.1007/s11227-015-1529-2

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