With the growth of Internet-based services, data centers must deal with increasing data traffic. Load-balancing technologies can help data centers process data effectively and stably; however, the current load-balancing methods do not take into account the heat generated by servers. Excessive heat can increase the failure rate of IT devices and the energy consumption of air conditioning systems, both of which lead to higher data center maintenance costs. This paper aims to simultaneously increase the coefficient of performance (COP) of the data center’s air-conditioning equipment and decrease the semiconductor-based equipment failure rate. To do so — and, consequently, reduce the operation and maintenance costs — we propose a novel request distribution system based on server-temperature and evaluate the proposed system by creating a thermal model of a data center. As a result, it is suggested that using the proposed load-balancing method the semiconductor failure rate can be reduced by 32 % when compared with the common round-robin distribution method, and by 19 % when compared with a load-balancing method based on CPU utilization. Moreover, the COP of the air-conditioning equipment obtained with the proposed method is recognized to be higher than those obtained with either the round-robin or the CPU-utilization-based methods.
- Electronic and Photonic Packaging Division
Temperature-Based Request Distribution for Effective CRAC and Equipment Life-Cycle Extension
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Nakajo, Y, & Nishi, H. "Temperature-Based Request Distribution for Effective CRAC and Equipment Life-Cycle Extension." Proceedings of the ASME 2017 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems collocated with the ASME 2017 Conference on Information Storage and Processing Systems. ASME 2017 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. San Francisco, California, USA. August 29–September 1, 2017. V001T02A014. ASME. https://doi.org/10.1115/IPACK2017-74341
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