Abstract
This paper puts forward a systematic approach to designing energy-aware traffic-efficient geographical load balancing schemes for data-center networks that are not only optimal, but also computationally efficient and amenable to distributed implementation. Under a stochastic optimization approach, we rely on decomposition techniques and develop a two-timescale algorithm that optimizes jointly workload and power balancing schemes across the network. Both delay-tolerant and interactive workloads are accommodated, and novel smart-grid features are incorporated to cope with renewables and energy storage units.
Original language | English (US) |
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Title of host publication | Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 |
Editors | Michael B. Matthews |
Publisher | IEEE Computer Society |
Pages | 795-799 |
Number of pages | 5 |
ISBN (Electronic) | 9781538639542 |
DOIs | |
State | Published - Mar 1 2017 |
Event | 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 - Pacific Grove, United States Duration: Nov 6 2016 → Nov 9 2016 |
Publication series
Name | Conference Record - Asilomar Conference on Signals, Systems and Computers |
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ISSN (Print) | 1058-6393 |
Other
Other | 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 |
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Country/Territory | United States |
City | Pacific Grove |
Period | 11/6/16 → 11/9/16 |
Bibliographical note
Funding Information:Work in this paper was supported by NSF grants 1509040, 1508993, 1423316, 1442686, by Spanish MINECO Grant TEC2013-41604-R and CAM Grant S2013/ICE-2933.
Publisher Copyright:
© 2016 IEEE.