Title :
Classified Power Capping with Distribution Trees in Cloud Computing
Author :
Wu, Zhengkai ; Zhang, Junyao ; Giles, Chris ; Wang, Jun
Author_Institution :
Dept. of EECS, Univ. of Central Florida, Orlando, FL, USA
Abstract :
Power management is becoming very important in data centers. Cloud computing is also one of the newest promising data center techniques which is appealing to many big companies. As cloud computing is different from current data centers in terms of power management due to a dynamic structure and property for its online service. Power budgeting, in terms of its important role in power management, provides powerful solutions for cloud computing with dynamic capabilities. To be specific, existing methods for data centers are based on power distribution units (PDU) divided by fixed locations on physical levels. However, it is not suitable for cloud with the dynamic property. We propose a power management design based at the logical level which uses a distribution tree with classified power capping by different service or workload types. By setting multiple trees, we can differentiate and analyze the effect of workload types and Service Level Agreements (SLAs) in terms of power characteristics.
Keywords :
cloud computing; computer centres; power aware computing; PDU; SLA; cloud computing; data centers; distribution trees; dynamic capabilities; dynamic structure; online service; power budgeting; power capping; power distribution units; power management; power management design; service level agreements; Cloud computing; Computers; Hardware; Peer to peer computing; Power demand; Power measurement; Servers; cloud computing; distribution trees; power capping;
Conference_Titel :
Networking, Architecture and Storage (NAS), 2011 6th IEEE International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-1-4577-1172-5
Electronic_ISBN :
978-0-7695-4509-7
DOI :
10.1109/NAS.2011.52