Abstract
Two IT-system control methods, which realize efficient battery usage for battery-powered IT systems targeting developing countries such as India, are proposed. The proposed methods control the IT equipment and cooling power collaboratively on the basis of a forecast of power outage duration. To quantitatively evaluate these methods, power outages in Bangalore, India, were measured. The proposed methods were evaluated by using this measured power outage data. According to the evaluation results, the proposed methods can improve a measure of battery efficiency, namely, IT-used-energy (Q t )/battery-used-energy (Q u ), by 39% compared to that of conventional IT systems.
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References
Pedram, M., Wu, Q.: Design Considerations for Battery-Powered Electronics. In: Proc. Design Automation Conf., pp. 861–866 (June 1999)
Lahiri, K., Raghunathan, A., Dey, S.: Battery-Driven System Design: A New Frontier in Low Power Design. In: Proc. Int’l Conf. VLSI Design/7th Asia and South Pacific Design Automation Conf., pp. 261–267 (2002)
Luo, J., Jha, N.K.: Battery-Aware Static Scheduling for Distributed Real-Time Embedded Systems. In: Proc. Design Automation Conf., pp. 444–449 (2001)
Chowdhury, P., Chakrabarti, C.: Static Task-scheduling Algorithms for Battery-powered DVS Systems. IEEE Trans. Very Large Scale Integr. (VLSI) Syst. 13, 226 (2005)
Ravi, N., Scott, J., Lu, H., Iftode, L.: Context-aware Battery Management for Mobile Phones. In: Proc. Conf. on Pervasive Computing and Communications, pp. 224–233 (2008)
Gmach, D., Rolia, J., Cherkasova, L., Kemper, A.: Workload Analysis and Demand Prediction of Enterprise Data Center Applications. In: Proc. of 10th Int’l Symp. on Workload Characterization, pp. 171–180 (September 2007)
Nicolescu, V., Gmach, D., Mohr, M., Kemper, A., Krcmar, H.: Evaluation of Adaptive Computing Concepts for Classical ERP Systems and Enterprise Services. In: Proc. CEC and EEE 2006, p. 48 (2006)
Gou, B., Wu, W.: Is the Prediction of Power System Blackouts Possible? In: Proc. Power and Energy Society General Meeting, pp. 1–4 (2008)
Panasonic Storage Battery Co., Ltd., LC-V1233 datasheet
Gold, S.: A PSPICE Macromodel for Lithium-Ion Batteries. In: The Battery Conference, pp. 215–222 (1997)
Hamilton, J.D.: Time Series Analysis. Princeton University Press, Princeton (1994)
Taylor, J.W.: Short-term Electricity Demand Forecasting Using Double Seasonal Exponential Smoothing. J. Oper. Res. Soc. 54, 799–805 (2003)
Hyndman, R., Khandakar, Y.: Automatic Time Series Forecasting: The forecast Package for R. Journal of Statistical Software 27(3) (2008)
Standard Performance Evaluation Corporation, http://www.spec.org/power_ssj2008/
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Matsumura, T., Yamada, T. (2012). IT-Cooling Collaborative Control Methods for Battery-Aware IT-Systems Targeting India. In: Auweter, A., Kranzlmüller, D., Tahamtan, A., Tjoa, A.M. (eds) ICT as Key Technology against Global Warming. ICT-GLOW 2012. Lecture Notes in Computer Science, vol 7453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32606-6_1
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DOI: https://doi.org/10.1007/978-3-642-32606-6_1
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