Abstract
For smart grid, multi-tenant data centers play a major part in the demand response program due to their large energy demand. Emergency demand response is critical in preserving the electrical infrastructure (i.e., the grid) in emergency situations, such as extreme weather events. Further economic demand response programs can stabilize the energy market by shifting the electricity demand to off-peak durations. This part of the book examines the motivations, issues, and challenges involved in multi-tenant data center demand response. Further, it summarizes the formulated problems and the possible solutions.
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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.
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.
Sun, Q., Wu, C., Ren, S., & Li, Z. (2015, June). Fair rewarding in colocation data centers: Truthful mechanism for emergency demand response. In IEEE 23rd international symposium on quality of service (IWQoS) (pp. 359–368). [Online]. Available: https://goo.gl/WesrxS.
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.
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.
Tran, N. H., Do, C. T., Hong, C. S., Ren, S., & Han, Z. (2015, November). Coordinated colocation datacenters for economic demand responce. SIGMETRICS Performance Evaluation Review, 43(3), 34–37. [Online]. Available: http://goo.gl/WtcQYZ.
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.
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.
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.
Moore, J., Chase, J., Ranganathan, P., & Sharma, R. (2005). Making scheduling “Cool”: Temperature-aware workload placement in data centers. In USENIX annual technical conference, ser. ATEC ’05 (pp. 5–5). Berkeley, CA, USA: USENIX Association. [Online]. Available: http://goo.gl/hMgS5G.
Ghatikar, G., Ganti, V., Matson, N., & Piette, M. A. (2012, August). Demand response opportunities and enabling technologies for data centers: Findings from field studies. Berkeley Lab, Berkeley, CA, Tech. Rep. LBNL-5763E. [Online]. Available: http://goo.gl/Z953FG.
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.
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.
Boyd, S. & Vandenberghe, L. (2004). Convex optimization. New York, NY: Cambridge University Press. [Online]. Available: http://goo.gl/3YTKaJ.
EnerNOC. (2009). Demand response: A multi-purpose resource for utilities and grid operations. Tech. Rep. [Online]. Available: http://goo.gl/atcj5N.
Ghamkhari, M. & Mohsenian-Rad, H. (2013, June). Energy and performance management of green data centers: A profit maximization approach. IEEE Transactions on Smart Grid, 4(2), 1017–1025. [Online]. Available: http://goo.gl/0chcuz.
Liu, Z., Liu, I., Low, S., & Wierman, A. (2014, June). Pricing data center demand response. SIGMETRICS Performance Evaluation Review, 42(1), 111–123. [Online]. Available: http://goo.gl/3K7Nca.
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).
Tang, Q., Mukherjee, T., Gupta, S. K. S., & Cayton, P. (2006, October). Sensor-based fast thermal evaluation model for energy efficient high-performance datacenters. In 4th international conference on intelligent sensing and information processing (pp. 203–208).
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Oo, T.Z., Tran, N.H., Ren, S., Hong, C.S. (2018). System Model. In: A Survey on Coordinated Power Management in Multi-Tenant Data Centers. Springer, Cham. https://doi.org/10.1007/978-3-319-66062-2_8
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DOI: https://doi.org/10.1007/978-3-319-66062-2_8
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