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Classified power capping by network distribution trees for green computing

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Abstract

Power management is becoming very important in data centers. To apply power management in cloud computing, Green Computing has been proposed and considered. Cloud computing is one of the new promising techniques, that are appealing to many big companies. In fact, due to its dynamic structure and property in online services, cloud computing differs from current data centers in terms of power management. To better manage the power consumption of web services in cloud computing with dynamic user locations and behaviors, we propose a power budgeting design based on the logical level, using distribution trees. By setting multiple trees or forest, we can differentiate and analyze the effect of workload types and Service Level Agreements (SLAs, e.g. response time) in terms of power characteristics. Based on these, we introduce classified power capping for different services as the control reference to maximize power saving when there are mixed workloads.

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Authors and Affiliations

  1. Department of EECS, University of Central Florida, Orlando, FL, USA

    Zhengkai Wu, Christopher Giles & Jun Wang

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  1. Zhengkai Wu
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  2. Christopher Giles
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  3. Jun Wang
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Correspondence to Zhengkai Wu.

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Wu, Z., Giles, C. & Wang, J. Classified power capping by network distribution trees for green computing. Cluster Comput 16, 17–26 (2013). https://doi.org/10.1007/s10586-011-0173-8

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  • DOI: https://doi.org/10.1007/s10586-011-0173-8

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