Skip to main content
Erschienen in: Journal of Network and Systems Management 1/2021

01.01.2021

A Data-driven, Multi-setpoint Model Predictive Thermal Control System for Data Centers

verfasst von: SeyedMorteza Mirhoseininejad, Ghada Badawy, Douglas G. Down

Erschienen in: Journal of Network and Systems Management | Ausgabe 1/2021

Einloggen

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper presents a system for jointly managing cooling units and workload assignment in modular data centers. The system aims to minimize power consumption while respecting temperature constraints, all in a thermally heterogeneous environment. Unlike traditional cooling controllers, which may over/under cool certain areas in the data center due to the use of a single setpoint, our framework does not have a single setpoint to satisfy. Instead, using a data-driven thermal model, the proposed system generates an optimal temperature map, the required temperature distribution matrix (RTDM), to be used by the controller, eliminating under/over cooling and improving power efficiency. The RTDM is the resulting temperature distribution when jointly considering workload assignment and cooling control. In addition, we propose the use of model predictive control (MPC) to regulate the operational variables of cooling units in a power-efficient fashion to comply with the RTDM. Within each iteration of the MPC loop, an optimization problem involving the thermal model is solved, and the underlying thermal model is updated. To prove the feasibility of the proposed power efficient system, it has been implemented on an actual modular data center in our facilities. Results from the implementation show the potential for considerable power savings compared to other control methods.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Shehabi, A., Smith, S.J., Masanet, E., Koomey, J.: Data center growth in the United States: decoupling the demand for services from electricity use. Environ. Res. Lett. 13(12), 1–12 (2018)CrossRef Shehabi, A., Smith, S.J., Masanet, E., Koomey, J.: Data center growth in the United States: decoupling the demand for services from electricity use. Environ. Res. Lett. 13(12), 1–12 (2018)CrossRef
2.
Zurück zum Zitat Umair, S., Muneer, U., Zahoor, M.N., Malik, A.W.: “Mobile cloud computing future trends and opportunities,” in Managing and Processing Big Data in Cloud Computing, pp. 105–120, IGI Global, (2016) Umair, S., Muneer, U., Zahoor, M.N., Malik, A.W.: “Mobile cloud computing future trends and opportunities,” in Managing and Processing Big Data in Cloud Computing, pp. 105–120, IGI Global, (2016)
3.
Zurück zum Zitat Klemick, H., Kopits, E., Wolverton, A.: How do data centers make energy-efficiency investment decisions? Qualitative evidence from focus groups and interviews. Energy Efficiency 12, 1359–1377 (June 2019)CrossRef Klemick, H., Kopits, E., Wolverton, A.: How do data centers make energy-efficiency investment decisions? Qualitative evidence from focus groups and interviews. Energy Efficiency 12, 1359–1377 (June 2019)CrossRef
4.
Zurück zum Zitat Varsamopoulos, G., Abbasi, Z., Gupta, S.K.: “Trends and effects of energy proportionality on server provisioning in data centers,” in 2010 International Conference on High Performance Computing, pp. 1–11, IEEE, (2010) Varsamopoulos, G., Abbasi, Z., Gupta, S.K.: “Trends and effects of energy proportionality on server provisioning in data centers,” in 2010 International Conference on High Performance Computing, pp. 1–11, IEEE, (2010)
5.
Zurück zum Zitat Dai, J., Ohadi, M.M., Das, D., Pecht, M.G.: Optimum cooling of data centers. Springer, New York (2016) Dai, J., Ohadi, M.M., Das, D., Pecht, M.G.: Optimum cooling of data centers. Springer, New York (2016)
6.
Zurück zum Zitat Sawyer, R.: “Calculating total power requirements for data centers, whitepaper,” in Power Conversion, pp. 1–10, Schneider Electric’s Data Center Science Center, (2004) Sawyer, R.: “Calculating total power requirements for data centers, whitepaper,” in Power Conversion, pp. 1–10, Schneider Electric’s Data Center Science Center, (2004)
7.
Zurück zum Zitat Loper, J., Parr, S.: Energy efficiency in data centers: a new policy frontier. Environ. Qual. Manag. 16(4), 83–97 (2007)CrossRef Loper, J., Parr, S.: Energy efficiency in data centers: a new policy frontier. Environ. Qual. Manag. 16(4), 83–97 (2007)CrossRef
8.
Zurück zum Zitat Sharma, R.K., Bash, C.E., Patel, C.D., Friedrich, R.J., Chase, J.S.: Balance of power: dynamic thermal management for Internet data centers. IEEE Internet Comput. 9(1), 42–49 (2005)CrossRef Sharma, R.K., Bash, C.E., Patel, C.D., Friedrich, R.J., Chase, J.S.: Balance of power: dynamic thermal management for Internet data centers. IEEE Internet Comput. 9(1), 42–49 (2005)CrossRef
9.
Zurück zum Zitat Chaudhry, M.T., Ling, T.C., Hussain, S.A., Manzoor, A.: Minimizing thermal stress for data center servers through thermal-aware relocation. Sci. World J. 2014, 1–9 (2014)CrossRef Chaudhry, M.T., Ling, T.C., Hussain, S.A., Manzoor, A.: Minimizing thermal stress for data center servers through thermal-aware relocation. Sci. World J. 2014, 1–9 (2014)CrossRef
10.
Zurück zum Zitat Moore, J.D., Chase, J.S., Ranganathan, P.: “Weatherman: Automated, online and predictive thermal mapping and management for data centers,” in Proceedings of the 3rd International Conference on Autonomic Computing, ICAC 2006, Dublin, Ireland, 13-16 June 2006, pp. 155–164, IEEE Computer Society, (2006) Moore, J.D., Chase, J.S., Ranganathan, P.: “Weatherman: Automated, online and predictive thermal mapping and management for data centers,” in Proceedings of the 3rd International Conference on Autonomic Computing, ICAC 2006, Dublin, Ireland, 13-16 June 2006, pp. 155–164, IEEE Computer Society, (2006)
11.
Zurück zum Zitat Bash, C., Forman, G.: “Cool job allocation: Measuring the power savings of placing jobs at cooling-efficient locations in the data center,” in 2007 USENIX Annual Technical Conference on Proceedings of the USENIX Annual Technical Conference, ECBS ’19, (USA), pp. 19:1–19:37, USENIX Association, (2007) Bash, C., Forman, G.: “Cool job allocation: Measuring the power savings of placing jobs at cooling-efficient locations in the data center,” in 2007 USENIX Annual Technical Conference on Proceedings of the USENIX Annual Technical Conference, ECBS ’19, (USA), pp. 19:1–19:37, USENIX Association, (2007)
12.
Zurück zum Zitat Abbasi, Z., Varsamopoulos, G., Gupta, S.: “TACOMA: Server and workload management in Internet data centers considering cooling-computing power trade-off and energy proportionality,” ACM Transactions on Architecture and Code Optimization (TACO), vol. 9, no. 2, pp. 11:1–11:37, (2012) Abbasi, Z., Varsamopoulos, G., Gupta, S.: “TACOMA: Server and workload management in Internet data centers considering cooling-computing power trade-off and energy proportionality,” ACM Transactions on Architecture and Code Optimization (TACO), vol. 9, no. 2, pp. 11:1–11:37, (2012)
13.
Zurück zum Zitat Tang, Q., Gupta, S.K.S., Varsamopoulos, G.: Energy-efficient thermal-aware task scheduling for homogeneous high-performance computing data centers: A cyber-physical approach. IEEE Trans. Parall. Distrib. Syst. 19, 1458–1472 (2008)CrossRef Tang, Q., Gupta, S.K.S., Varsamopoulos, G.: Energy-efficient thermal-aware task scheduling for homogeneous high-performance computing data centers: A cyber-physical approach. IEEE Trans. Parall. Distrib. Syst. 19, 1458–1472 (2008)CrossRef
14.
Zurück zum Zitat Nadjahi, C., Louahlia, H., Lemasson, S.: A review of thermal management and innovative cooling strategies for data center. Sustain. Comput. 19, 14–28 (2018) Nadjahi, C., Louahlia, H., Lemasson, S.: A review of thermal management and innovative cooling strategies for data center. Sustain. Comput. 19, 14–28 (2018)
15.
Zurück zum Zitat Chainer, T., Schultz, M., Parida, P., Gaynes, M.: Improving data center energy efficiency with advanced thermal management. IEEE Trans. Comp. Pack. Manuf. Technol. 7, 1228–1239 (2017) Chainer, T., Schultz, M., Parida, P., Gaynes, M.: Improving data center energy efficiency with advanced thermal management. IEEE Trans. Comp. Pack. Manuf. Technol. 7, 1228–1239 (2017)
16.
Zurück zum Zitat Khalaj, A., Halgamuge, S.: A review on efficient thermal management of air-and liquid-cooled data centers: From chip to the cooling system. Appl. Energy 205, 1165–1188 (2017)CrossRef Khalaj, A., Halgamuge, S.: A review on efficient thermal management of air-and liquid-cooled data centers: From chip to the cooling system. Appl. Energy 205, 1165–1188 (2017)CrossRef
18.
Zurück zum Zitat Durand-Estebe, B., Le Bot, C., Mancos, J.N., Arquis, E.: Data center optimization using PID regulation in CFD simulations. Energy and Buildings 66, 154–164 (2013)CrossRef Durand-Estebe, B., Le Bot, C., Mancos, J.N., Arquis, E.: Data center optimization using PID regulation in CFD simulations. Energy and Buildings 66, 154–164 (2013)CrossRef
19.
Zurück zum Zitat Rivera, D.E., Morari, M., Skogestad, S.: Internal model control: PID controller design. Ind. Eng. Chem. Process Design Dev. 25(1), 252–265 (1986)CrossRef Rivera, D.E., Morari, M., Skogestad, S.: Internal model control: PID controller design. Ind. Eng. Chem. Process Design Dev. 25(1), 252–265 (1986)CrossRef
20.
Zurück zum Zitat Kheradmandi, M., Down, D.G., Moazamigoodarzi, H.: “Energy-efficient data-based zonal control of temperature for data centers,” in 2019 Tenth International Green and Sustainable Computing Conference (IGSC), pp. 1–7, Oct (2019) Kheradmandi, M., Down, D.G., Moazamigoodarzi, H.: “Energy-efficient data-based zonal control of temperature for data centers,” in 2019 Tenth International Green and Sustainable Computing Conference (IGSC), pp. 1–7, Oct (2019)
21.
Zurück zum Zitat Garcia, C.E., Prett, D.M., Morari, M.: Model predictive control: theory and practice: a survey. Automatica 25(3), 335–348 (1989)CrossRef Garcia, C.E., Prett, D.M., Morari, M.: Model predictive control: theory and practice: a survey. Automatica 25(3), 335–348 (1989)CrossRef
23.
Zurück zum Zitat Lazic, N., Boutilier, C., Lu, T., Wong, E., Roy, B., Ryu, M., Imwalle, G.: “Data center cooling using model-predictive control,” In Advances in Neural Information Processing Systems, pp. 3814–3823, (2018) Lazic, N., Boutilier, C., Lu, T., Wong, E., Roy, B., Ryu, M., Imwalle, G.: “Data center cooling using model-predictive control,” In Advances in Neural Information Processing Systems, pp. 3814–3823, (2018)
24.
Zurück zum Zitat Beghi, A., Lionello, M., Rampazzo, M.: “Efficient operation of indirect evaporative data center cooling systems via newton-like extremum-seeking control,” In 2019 IEEE Conference on Control Technology and Applications (CCTA), pp. 424–429, Aug (2019) Beghi, A., Lionello, M., Rampazzo, M.: “Efficient operation of indirect evaporative data center cooling systems via newton-like extremum-seeking control,” In 2019 IEEE Conference on Control Technology and Applications (CCTA), pp. 424–429, Aug (2019)
25.
Zurück zum Zitat Zhou, R., Bash, C., Wang, Z., McReynolds, A., Christian, T., Cader, T.: “Data center cooling efficiency improvement through localized and optimized cooling resources delivery,” ASME International Mechanical Engineering Congress and Exposition, vol. Volume 7: Fluids and Heat Transfer, Parts A, B, C, and D, pp. 1789–1796, 11 (2012) Zhou, R., Bash, C., Wang, Z., McReynolds, A., Christian, T., Cader, T.: “Data center cooling efficiency improvement through localized and optimized cooling resources delivery,” ASME International Mechanical Engineering Congress and Exposition, vol. Volume 7: Fluids and Heat Transfer, Parts A, B, C, and D, pp. 1789–1796, 11 (2012)
26.
Zurück zum Zitat Feng, J.D., Chuang, F., Borrelli, F., Bauman, F.: Model predictive control of radiant slab systems with evaporative cooling sources. Energy Buildings 87, 199–210 (2015)CrossRef Feng, J.D., Chuang, F., Borrelli, F., Bauman, F.: Model predictive control of radiant slab systems with evaporative cooling sources. Energy Buildings 87, 199–210 (2015)CrossRef
27.
Zurück zum Zitat Kelman, A., Borrelli, F.: Bilinear model predictive control of a HVAC system using sequential quadratic programming. IFAC Proc. Vol. 44(1), 9869–9874 (2011)CrossRef Kelman, A., Borrelli, F.: Bilinear model predictive control of a HVAC system using sequential quadratic programming. IFAC Proc. Vol. 44(1), 9869–9874 (2011)CrossRef
28.
Zurück zum Zitat Ma, Y., Borrelli, F., Hencey, B., Coffey, B., Bengea, S., Haves, P.: Model predictive control for the operation of building cooling systems. IEEE Trans. Control Syst. Technol. 20(3), 796–803 (2011) Ma, Y., Borrelli, F., Hencey, B., Coffey, B., Bengea, S., Haves, P.: Model predictive control for the operation of building cooling systems. IEEE Trans. Control Syst. Technol. 20(3), 796–803 (2011)
29.
Zurück zum Zitat Ma, Y., Kelman, A., Daly, A., Borrelli, F.: Predictive control for energy efficient buildings with thermal storage: Modeling, stimulation, and experiments. IEEE Contr. Syst. Mag. 32(1), 44–64 (2012)CrossRef Ma, Y., Kelman, A., Daly, A., Borrelli, F.: Predictive control for energy efficient buildings with thermal storage: Modeling, stimulation, and experiments. IEEE Contr. Syst. Mag. 32(1), 44–64 (2012)CrossRef
30.
Zurück zum Zitat Gupta, R., Moazamigoodarzi, H., MirhoseiniNejad, S., Down, D.G., Puri, I.K.: Workload management for air-cooled data centers: an energy and exergy based approach. Energy 209, 118485 (2020)CrossRef Gupta, R., Moazamigoodarzi, H., MirhoseiniNejad, S., Down, D.G., Puri, I.K.: Workload management for air-cooled data centers: an energy and exergy based approach. Energy 209, 118485 (2020)CrossRef
31.
Zurück zum Zitat Bergman, T.L., Incropera, F.P., DeWitt, D.P., Lavine, A.S.: Fundamentals of heat and mass transfer. Wiley, New Jersey (2011) Bergman, T.L., Incropera, F.P., DeWitt, D.P., Lavine, A.S.: Fundamentals of heat and mass transfer. Wiley, New Jersey (2011)
32.
Zurück zum Zitat Moazamigoodarzi, H., Pal, S., Ghosh, S., Puri, I.K.: Real-time temperature predictions in IT server enclosures. Int. J. Heat Mass Transf. 127, 890–900 (2018)CrossRef Moazamigoodarzi, H., Pal, S., Ghosh, S., Puri, I.K.: Real-time temperature predictions in IT server enclosures. Int. J. Heat Mass Transf. 127, 890–900 (2018)CrossRef
33.
Zurück zum Zitat Li, L., Liang, C.-J.M., Liu, J., Nath, S., Terzis, A., Faloutsos, C.: “Thermocast: A cyber-physical forecasting model for datacenters,” in Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’11, (New York, NY, USA), pp. 1370–1378, ACM, 2011 Li, L., Liang, C.-J.M., Liu, J., Nath, S., Terzis, A., Faloutsos, C.: “Thermocast: A cyber-physical forecasting model for datacenters,” in Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’11, (New York, NY, USA), pp. 1370–1378, ACM, 2011
34.
Zurück zum Zitat Grishina, A., Chinnici, M., Kor, A.-L., Rondeau, E., Georges, J.-P.: A machine learning solution for data center thermal characteristics analysis. Energies 13, 4378 (2020)CrossRef Grishina, A., Chinnici, M., Kor, A.-L., Rondeau, E., Georges, J.-P.: A machine learning solution for data center thermal characteristics analysis. Energies 13, 4378 (2020)CrossRef
35.
Zurück zum Zitat MirhoseiniNejad, S., García, F.M., Badawy, G., Down, D.G.: “ALTM: Adaptive learning-based thermal model for temperature predictions in data centers,” in 2019 IEEE Sustainability through ICT Summit (StICT), pp. 1–6, IEEE, (2019) MirhoseiniNejad, S., García, F.M., Badawy, G., Down, D.G.: “ALTM: Adaptive learning-based thermal model for temperature predictions in data centers,” in 2019 IEEE Sustainability through ICT Summit (StICT), pp. 1–6, IEEE, (2019)
36.
Zurück zum Zitat Mauro, D., Schmidt, K.: Essential SNMP: Help for System and Network Administrators. “ O’Reilly Media, Inc.”, (2005) Mauro, D., Schmidt, K.: Essential SNMP: Help for System and Network Administrators. “ O’Reilly Media, Inc.”, (2005)
39.
Zurück zum Zitat LaCroix, J.: Mastering Ubuntu Server: Master the art of deploying, configuring, managing, and troubleshooting Ubuntu Server 1804. Packt Publishing Ltd, Birmingham (2018) LaCroix, J.: Mastering Ubuntu Server: Master the art of deploying, configuring, managing, and troubleshooting Ubuntu Server 1804. Packt Publishing Ltd, Birmingham (2018)
40.
Zurück zum Zitat MirhoseiniNejad, S., Moazamigoodarzi, H., Badawy, G., Down, D.G.: Joint data center cooling and workload management: a thermal-aware approach. Fut. Gen. Comput. Syst. 104, 174–186 (2020)CrossRef MirhoseiniNejad, S., Moazamigoodarzi, H., Badawy, G., Down, D.G.: Joint data center cooling and workload management: a thermal-aware approach. Fut. Gen. Comput. Syst. 104, 174–186 (2020)CrossRef
41.
Zurück zum Zitat Badea, A., Halunga, S., Luca, G.: “Energy optimization for the low data rate iot devices by using Manchester’s coded pseudo-random sequences,” In Proceedings of the 6th Conference on the Engineering of Computer Based Systems, ECBS ’19, (New York, NY, USA), pp. 19:1–19:4, ACM, 2019 Badea, A., Halunga, S., Luca, G.: “Energy optimization for the low data rate iot devices by using Manchester’s coded pseudo-random sequences,” In Proceedings of the 6th Conference on the Engineering of Computer Based Systems, ECBS ’19, (New York, NY, USA), pp. 19:1–19:4, ACM, 2019
42.
Zurück zum Zitat MirhoseiniNejad, S., Badawy, G., Down, D.G.: “EAWA: Energy-aware workload assignment in data centers,” in 2018 International Conference on High Performance Computing & Simulation (HPCS), pp. 260–267, IEEE, (2018) MirhoseiniNejad, S., Badawy, G., Down, D.G.: “EAWA: Energy-aware workload assignment in data centers,” in 2018 International Conference on High Performance Computing & Simulation (HPCS), pp. 260–267, IEEE, (2018)
43.
Zurück zum Zitat Zanin, A.C., De Gouvea, M.T., Odloak, D.: Integrating real-time optimization into the model predictive controller of the FCC system. Contr. Eng. Pract. 10(8), 819–831 (2002)CrossRef Zanin, A.C., De Gouvea, M.T., Odloak, D.: Integrating real-time optimization into the model predictive controller of the FCC system. Contr. Eng. Pract. 10(8), 819–831 (2002)CrossRef
44.
Zurück zum Zitat De Souza, G., Odloak, D., Zanin, A.C.: Real time optimization (RTO) with model predictive control (MPC). Comput. Chem. Eng. 34(12), 1999–2006 (2010)CrossRef De Souza, G., Odloak, D., Zanin, A.C.: Real time optimization (RTO) with model predictive control (MPC). Comput. Chem. Eng. 34(12), 1999–2006 (2010)CrossRef
45.
Zurück zum Zitat Edwards, C., Spurgeon, S.: Sliding mode control: theory and applications. CRC Press, New York (1998)CrossRef Edwards, C., Spurgeon, S.: Sliding mode control: theory and applications. CRC Press, New York (1998)CrossRef
Metadaten
Titel
A Data-driven, Multi-setpoint Model Predictive Thermal Control System for Data Centers
verfasst von
SeyedMorteza Mirhoseininejad
Ghada Badawy
Douglas G. Down
Publikationsdatum
01.01.2021
Verlag
Springer US
Erschienen in
Journal of Network and Systems Management / Ausgabe 1/2021
Print ISSN: 1064-7570
Elektronische ISSN: 1573-7705
DOI
https://doi.org/10.1007/s10922-020-09574-5

Weitere Artikel der Ausgabe 1/2021

Journal of Network and Systems Management 1/2021 Zur Ausgabe