Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 170 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 35 tok/s Pro
GPT-5 High 26 tok/s Pro
GPT-4o 115 tok/s Pro
Kimi K2 182 tok/s Pro
GPT OSS 120B 446 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Dynamic Provisioning in Next-Generation Data Centers with On-site Power Production (1303.6775v2)

Published 27 Mar 2013 in cs.DS and cs.SY

Abstract: The critical need for clean and economical sources of energy is transforming data centers that are primarily energy consumers to also energy producers. We focus on minimizing the operating costs of next-generation data centers that can jointly optimize the energy supply from on-site generators and the power grid, and the energy demand from servers as well as power conditioning and cooling systems. We formulate the cost minimization problem and present an offline optimal algorithm. For "on-grid" data centers that use only the grid, we devise a deterministic online algorithm that achieves the best possible competitive ratio of $2-\alpha_{s}$, where $\alpha_{s}$ is a normalized look-ahead window size. For "hybrid" data centers that have on-site power generation in addition to the grid, we develop an online algorithm that achieves a competitive ratio of at most \textmd{\normalsize {\small $\frac{P_{\max} (2-\alpha_{s})}{c_{o}+c_{m}/L} [1+2\frac{P_{\max}-c_{o}}{P_{\max}(1+\alpha_{g})}]$}}, where $\alpha_{s}$ and $\alpha_{g}$ are normalized look-ahead window sizes, $P_{\max}$ is the maximum grid power price, and $L$, $c_{o}$, and $c_{m}$ are parameters of an on-site generator. Using extensive workload traces from Akamai with the corresponding grid power prices, we simulate our offline and online algorithms in a realistic setting. Our offline (resp., online) algorithm achieves a cost reduction of 25.8% (resp., 20.7%) for a hybrid data center and 12.3% (resp., 7.3%) for an on-grid data center. The cost reductions are quite significant and make a strong case for a joint optimization of energy supply and energy demand in a data center. A hybrid data center provides about 13% additional cost reduction over an on-grid data center representing the additional cost benefits that on-site power generation provides over using the grid alone.

Citations (34)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.