Abstract
A systematic framework is put forth in this paper to integrate renewable energy sources (RES), distributed storage units, cooling facilities, as well as dynamic pricing into the workload and energy management tasks for a data center network. To cope with RES uncertainty, the resource allocation task is formulated as a robust optimization problem minimizing the worst-case net cost. The resulting problem is reformulated as a convex program, and then solved in a distributed fashion using the dual decomposition approach. Numerical tests demonstrate the performance gain of the proposed approach over the existing alternative.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3526-3530 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781479999880 |
| DOIs | |
| State | Published - May 18 2016 |
| Event | 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China Duration: Mar 20 2016 → Mar 25 2016 |
Publication series
| Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
|---|---|
| Volume | 2016-May |
| ISSN (Print) | 1520-6149 |
Other
| Other | 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 |
|---|---|
| Country/Territory | China |
| City | Shanghai |
| Period | 3/20/16 → 3/25/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Geo-distributed data centers
- cloud computing
- renewable energy
- robust optimization
- smart grid
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