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Managing energy and server resources in hosting centers
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Source ACM Symposium on Operating Systems Principles archive
Proceedings of the eighteenth ACM symposium on Operating systems principles table of contents
Banff, Alberta, Canada
SESSION: Resource management table of contents
Pages: 103 - 116  
Year of Publication: 2001
ISBN:1-58113-389-8
Also published in ...
Authors
Jeffrey S. Chase  Duke University
Darrell C. Anderson  Duke University
Prachi N. Thakar  Duke University
Amin M. Vahdat  Duke University
Ronald P. Doyle  Application Integation and Middleware, IBM Research Triangle Park
Sponsor
SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 42,   Downloads (12 Months): 273,   Citation Count: 127
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ABSTRACT

Internet hosting centers serve multiple service sites from a common hardware base. This paper presents the design and implementation of an architecture for resource management in a hosting center operating system, with an emphasis on energy as a driving resource management issue for large server clusters. The goals are to provision server resources for co-hosted services in a way that automatically adapts to offered load, improve the energy efficiency of server clusters by dynamically resizing the active server set, and respond to power supply disruptions or thermal events by degrading service in accordance with negotiated Service Level Agreements (SLAs).Our system is based on an economic approach to managing shared server resources, in which services "bid" for resources as a function of delivered performance. The system continuously monitors load and plans resource allotments by estimating the value of their effects on service performance. A greedy resource allocation algorithm adjusts resource prices to balance supply and demand, allocating resources to their most efficient use. A reconfigurable server switching infrastructure directs request traffic to the servers assigned to each service. Experimental results from a prototype confirm that the system adapts to offered load and resource availability, and can reduce server energy usage by 29% or more for a typical Web workload.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  128

Collaborative Colleagues:
Jeffrey S. Chase: colleagues
Darrell C. Anderson: colleagues
Prachi N. Thakar: colleagues
Amin M. Vahdat: colleagues
Ronald P. Doyle: colleagues