Power Cost Reduction in Distributed Data Centers: A Two-Time-Scale Approach for Delay Tolerant Workloads

This paper considers a stochastic optimization approach for job scheduling and server management in large-scale, geographically distributed data centers. Randomly arriving jobs are routed to a choice of servers. The number of active servers depends on server activation decisions that are updated at...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems 2014-01, Vol.25 (1), p.200-211
Main Authors: Yuan Yao, Longbo Huang, Sharma, Abhishek B., Golubchik, Leana, Neely, Michael J.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
data center
Delay
Distributed databases
Optimization
performance analysis
Power management
Routing
Servers
stochastic optimization
Vectors
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Summary:This paper considers a stochastic optimization approach for job scheduling and server management in large-scale, geographically distributed data centers. Randomly arriving jobs are routed to a choice of servers. The number of active servers depends on server activation decisions that are updated at a slow time scale, and the service rates of the servers are controlled by power scaling decisions that are made at a faster time scale. We develop a two-time-scale decision strategy that offers provable power cost and delay guarantees. The performance and robustness of the approach is illustrated through simulations.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2012.341