Internet of Things Based on Smart Objects pp 181-198 | Cite as
Experiments with a Sensing Platform for High Visibility of the Data Center
- 4.1k Downloads
Abstract
Data centers are large energy consumers and a substantial portion of this power consumption is due to the control of physical parameters, which bring the need of high efficiency environmental control systems. In this work, we describe a hardware sensing platform specifically tailored to collect physical parameters (temperature, pressure, humidity and power consumption) in large data centers. Our system architecture is composed of Smart Objects, the datacenter racks, that cooperate to contribute for the overall goal of finding opportunities to optimize energy consumption and achieving energy-efficient data centers. We also introduce an analysis of the delay to obtain the sensing data from the sensor network. This analysis provides an insight into the time scales supported by our platform, and also allows to study the delay for different data center topologies. Finally, we exemplify some capabilities of the system with a real deployment.
Keywords
Sensor Network Sensor Node Data Center Smart Object Dynamic Voltage ScalingNotes
Acknowledgments
This work was supported by National Funds through the FCT-MCTES (Portuguese Foundation for Science and Technology) and by ERDF (European Regional Development Fund) through COMPETE (Operational Programme ‘The- matic Factors of Competitiveness’), within projects Ref. FCOMP-01-0124-FEDER-022701 (CISTER), FCOMP-01- 0124-FEDER-012988 (SENODs) and FCOMP-01-0124-FEDER-020312 (SMARTSKIN).
References
- 1.Google. Google’s Green Data Centers : Network POP Case StudyGoogle Scholar
- 2.Brey, T., Lembke, P., Prisco, J., Abbott, K., Cortese, D., Hazelrigg, K., Larson, J., Shaffer, S., North, T., Darby, T.: Case Study: The ROI of Cooling System Energy Efficiency UpgradesGoogle Scholar
- 3.Michael, A.M., Paleczny, M.: Load Balancing Tasks in a Data Center Based on Pressure Differential Needed for Cooling Servers (2012)Google Scholar
- 4.TC ASHRAE. 2011 thermal guidelines for data processing environments expanded data center classes and usage guidance. ASHRAE, pp 1–45 (2011)Google Scholar
- 5.Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)Google Scholar
- 6.Fortino, G., Guerrieri, A., Lacopo, M., Lucia, M., Russo, W.: An agent-based middleware for cooperating smart objects. In: Highlights on Practical Applications of Agents and Multi-Agent Systems, pp. 387–398. Springer, New York (2013)Google Scholar
- 7.Fortino, G., Guerrieri, A., Russo, W., Savaglio, C.: Middlewares for smart objects and smart environments: overview and comparison. In: Internet of Things Based on Smart Objects, Technology, Middleware and Applications, Internet of Things. Springer. isbn: 978-3-319-00490-7 (2014)Google Scholar
- 8.Kawsar, F., Nakajima, T., Park, J.H., Yeo, S.-S.: Design and implementation of a framework for building distributed smart object systems. J. Supercomput. 54(1), 4–28 (2010)Google Scholar
- 9.Pereira, N., Tenina, S., Tovar, E.: A microscope for the data center. In: Wireless Algorithms, Systems, and Applications, pp. 619–630, Springer (2012)Google Scholar
- 10.Parolini, L., Sinopoli, B., Krogh, B.H.: Reducing data center energy consumption via coordinated cooling and load management. In: Proceedings of the 2008 Conference on Power Aware Computing and Systems, HotPower’08, pp. 14–14, Berkeley, CA, USA (2008). USENIX AssociationGoogle Scholar
- 11.Zhou, R., Wang, Z., Bash, C.E., McReynolds, A.: Data center cooling management and analysis—a model based approach. In: 28 Annual Semiconductor Thermal Measurement, Modeling and Management Symposium (SEMI-THERM), San Jose, California, USA (2012)Google Scholar
- 12.Bohrer, P., Elnozahy, E.N., Keller, T., Kistler, M., Lefurgy, C., McDowell, C., Rajamony, R.: Chapter the case for power management in web servers, In: Melhem, R., Graybillpp, R. (eds.) Power aware computing. pp. 261–289. Kluwer Academic Publishers, Norwell (2002)Google Scholar
- 13.Tibor, H., Tarek, A., Kevin, S., Xue, L.: Dynamic voltage scaling in multitier web servers with end-to-end delay control. IEEE Trans. Comput. 56(4), 444–458 (2007)Google Scholar
- 14.Xu, R., Zhu, D., Rusu, C., Melhem, R., Mossé D.: Energy-efficient policies for embedded clusters. In: Proceedings of the 2005 ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems, LCTES ’05, pp. 1–10, New York, NY, USA (2005). ACMGoogle Scholar
- 15.Meisner, D., Gold, B.T., Wenisch, T.F.: Powernap: eliminating server idle power. In: Proceedings of the 14th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS ’09, pp. 205–216, New York, NY, USA (2009) ACMGoogle Scholar
- 16.Wang, S., Chen, J.-J., Liu J., Liu, X.: Power saving design for servers under response time constraint. In: Proceedings of the 2010 22nd Euromicro Conference on Real-Time Systems, ECRTS ’10, pp. 123–132, Washington, DC, USA (2010). IEEE Computer SocietyGoogle Scholar
- 17.Jeffrey, R., Yogendra, J.: Modeling of data center airflow and heat transfer: state of the art and future trends. Distrib. Parallel Dat. 21(2–3), 193–225 (2007)Google Scholar
- 18.Liang C.-J.M., Liu, J., Luo, L., Terzis, A., Zhao F.: Racnet: a high-fidelity data center sensing network. In: Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, SenSys ’09, pp. 15–28, New York, NY, USA (2009). ACMGoogle Scholar
- 19.Weiss, B., Truong, H.L., Schott, W., Scherer, T., Lombriser, C., Chevillat, P.: Wireless sensor network for continuously monitoring temperatures in data centers. IBM RZ 3807 (2011)Google Scholar
- 20.Schmidt, R.R., Cruz, E.E., Iyengar, M.: Challenges of data center thermal management. IBM J. Res. Dev. 49(4.5):709–723 (2005)Google Scholar
- 21.Karlsson, J.F., Moshfegh, B.: Investigation of indoor climate and power usage in a data center. Energ Buildings 37(10), 1075–1083 (2005)Google Scholar
- 22.Viswanathan, H., Lee, E.K., Pompili, D.: Self-organizing sensing infrastructure for autonomic management of green datacenters. IEEE Netw. 25(4):34–40 (2011)Google Scholar
- 23.Lenchner, J., Isci, C., Kephart, J.O., Mansley, C., Connell, J., McIntosh, S.: Towards data center self-diagnosis using a mobile robot. In: Towards data center self-diagnosis using a mobile robot, pp. 81–90 (2011). ACMGoogle Scholar
- 24.Modbus over serial line—specification & implementation guide—v1.0. http://www.modbus.org/docs/Modbus_over_serial_line_V1.pdf (2002)
- 25.Latré, B., De Mil P., Moerman, I., Dhoedt, B., Demeester, P., Van Dierdonck N.: Throughput and delay analysis of unslotted IEEE 802.15.4. JNW 1(1):20–28 (2006)Google Scholar
- 26.Measuring effective capacity of IEEE 802.15.4 beaconless mode, volume 1, (2006)Google Scholar
- 27.IEEE. IEEE standard for information technology—telecommunications and information exchange between systems—local and metropolitan area networks—specific requirements - part 14.4: Wireless medium access control (MAC) and physical layer (PHY) specifications for low rate wireless personal area networks (LR-WPANs), October (2003)Google Scholar
- 28.Chipcon. CC2420 datasheet. http://www.chipcon.com/files/CC2420/Data///Sheet/1/3.pdf