Power Control by Distribution Tree with Classified Power Capping in Cloud Computing

  • Authors:
  • Zhengkai Wu;Jun Wang

  • Affiliations:
  • -;-

  • Venue:
  • GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
  • Year:
  • 2010

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Abstract

Power management is becoming very important in data centers. Cloud computing is also one of the newer promising techniques, that are appealing to many big companies. To apply power management in cloud computing has been proposed and considered as green computing. Cloud computing, due to its dynamic structure and property in online services, 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 a distribution tree. By setting multiple trees, we can differentiate and analyze the effect of workload types and Service Level Agreements (SLAs, e.g. response time) in terms of power characteristics. Base on these, we introduce classified power capping for different services as the control reference to maximize power saving when there are mixed workloads.