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Journal ArticleDOI

Uncovering energy-efficiency opportunities in data centers

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TLDR
A mobile measurement technology for optimizing the space and energy efficiency of DCs is presented and the combination of these two data types, in conjunction with innovative modeling techniques, provides the basis for extending the MMT concept toward an interactive energy management solution.
Abstract
The combination of rapidly increasing energy use of data centers (DCs), which is triggered by dramatic increases in IT (information technology) demands, and increases in energy costs and limited energy supplies has made the energy efficiency of DCs a central concern from both a cost and a sustainability perspective This paper describes three important technology components that address the energy consumption in DCs First, we present a mobile measurement technology (MMT) for optimizing the space and energy efficiency of DCs The technology encompasses the interworking of an advanced metrology technique for rapid data collection at high spatial resolution and measurement-driven modeling techniques, enabling optimal adjustments of a DC environment within a target thermal envelope Specific example data demonstrating the effectiveness of MMT is shown Second, the static MMT measurements obtained at high spatial resolution are complemented by and integrated with a real-time sensor network The requirements and suitable architectures for wired and wireless sensor solutions are discussed Third, an energy and thermal model analysis for a DC is presented that exploits both the high-spatial-resolution (but static) MMT data and the high-timeresolved (but sparse) sensor data The combination of these two data types (static and dynamic), in conjunction with innovative modeling techniques, provides the basis for extending the MMT concept toward an interactive energy management solution

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Citations
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Journal ArticleDOI

Data Center Energy Consumption Modeling: A Survey

TL;DR: An in-depth study of the existing literature on data center power modeling, covering more than 200 models, organized in a hierarchical structure with two main branches focusing on hardware-centric and software-centric power models.
Journal ArticleDOI

State-of-the-art research study for green cloud computing

TL;DR: This paper study state-of-the-art techniques and research related to power saving in the IaaS of a cloud computing system, which consumes a huge part of total energy in a cloud Computing system.
Journal ArticleDOI

Advances in data center thermal management

TL;DR: In this article, a review of the state-of-the-art in data center thermal management is presented, with a focus on real-time measurement & control, model validation and heuristics based optimization.
Proceedings ArticleDOI

TAPO: Thermal-aware power optimization techniques for servers and data centers

TL;DR: Two hierarchical thermal-aware power optimization techniques that are complementary to each other and achieve (i) lower overall system power with no performance penalty or (ii) higher performance within the same power budget are proposed.
Patent

Knowledge-based models for data centers

TL;DR: In this paper, a method for modeling thermal distributions in a data center is provided, where the vertical temperature distribution data for each of the locations is plotted as an s curve, and each of these s curves is represented with a set of parameters that characterize the shape of the s curve.
References
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Proceedings ArticleDOI

Comparison Between Numerical and Experimental Temperature Distributions in a Small Data Center Test Cell

TL;DR: In this article, the authors used a simulated server rack in a small room where detailed temperature (3D), flow, and power measurements were carried out for a single scenario under steady state conditions.
Journal ArticleDOI

Optimizing thermal design of data center cabinets with a new multi-objective genetic algorithm

TL;DR: It is shown that in optimizing the data center cabinet problem, the new MOGA outperforms a conventional MogA by estimating the Pareto front using 50% fewer simulation calls, which makes its use very promising for complex thermal design problems.