Local Cooling Control of Data Centers With Adaptive Vent Tiles

2009 ◽  
Author(s):  
Monem H. Beitelmal ◽  
Zhikui Wang ◽  
Carlos Felix ◽  
Cullen Bash ◽  
Christopher Hoover ◽  
...  
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Dynamic Models ◽  
Algorithm Design ◽  
Local Cooling ◽  
Fine Grained ◽  
Airflow Distribution ◽  
Equipment Configuration ◽  
Tile Flow ◽  
Configuration Changes

Local airflow distribution in data center environments has historically been accomplished through ventilation tiles distributed over a raised floor air distribution plenum. The tiles are initially configured upon the commissioning of the facility and, as IT equipment configuration changes with time, the tiles are adjusted accordingly. However, tile adjustment is a manual process that is error-prone and often non-intuitive. Tile flow rates are a strong function of under floor plenum pressure distribution which is subject to change as tile layouts are reconfigured. Thermal models are often developed to assist with layout changes, but these models can be time-consuming to generate and require skilled users to achieve accurate results. This paper presents an adaptive vent tile (AVT) for use in raised floor data centers that can adapt to the needs of nearby IT equipment. We present a multi-input-multi-output (MIMO) AVT controller that automatically and dynamically adjusts a multiplicity of AVT openings in coordination such that thermal management requirements are met with minimum use of airflow. We describe the development of dynamic models and algorithm design of the MIMO controller. The controller was evaluated with a set of AVT units in a production data center environment. Results show that the controller can optimize local airflow distribution, provide fine-grained rack intake temperature control and respond to disturbances in a manner that is not achievable through static distribution of tiles.

Techniques for Controlling Airflow Distribution in Raised-Floor Data Centers

2003 ◽  
Author(s):  
Kailash C. Karki ◽  
Suhas V. Patankar ◽  
Amir Radmehr
Keyword(s):  
Mathematical Model ◽  
Data Center ◽  
Heat Load ◽  
Data Centers ◽  
Open Area ◽  
Flow Rates ◽  
Airflow Distribution ◽  
Wide Range ◽  
Optimum Utilization ◽  
Load Pattern

In raised-floor data centers, the airflow rates through the perforated tiles must meet the cooling requirements of the computer servers placed next to the tiles. The data centers house a wide range of equipment, and the heat load pattern on the floor can be quite arbitrary and changes as the data center evolves. To achieve optimum utilization of the floor space and the flexibility for rearrangement and retrofitting, the designers and managers of data centers must be able to modify the airflow rates through the perforated tiles. The airflow rates through the perforated tiles are governed primarily by the pressure distribution under the raised floor. Thus, the key to modifying the flow rates is to influence the flow field in the plenum. This paper discusses a number of techniques that can be used for controlling airflow distribution. These techniques involve changing the plenum height and open area of perforated tiles, and installing thin (solid and perforated) partitions in the plenum. A number of case studies, using a mathematical model, are presented to demonstrate the effectiveness of these techniques.

scholarly journals A Non-Intrusive, Traffic-Aware Prediction Framework for Power Consumption in Data Center Operations

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 663
Author(s):  
Zheng Liu ◽  
Mian Zhang ◽  
Xusheng Zhang ◽  
Yun Li
Keyword(s):  
Power Consumption ◽  
Prediction Model ◽  
Data Center ◽  
Data Centers ◽  
Prediction Performance ◽  
Coarse Grained ◽  
Fine Grained ◽  
Encoding Strategy ◽  
Power Consumption Prediction ◽  
Consumption Prediction

Modern cloud computing relies heavily on data centers, which usually host tens of thousands of servers. Predicting the power consumption accurately in data center operations is crucial for energy optimization. In this paper, we formulate the power consumption prediction at both the fine-grained and coarse-grained level. We carefully discuss the desired properties of an applicable prediction model and propose a non-intrusive, traffic-aware prediction framework for power consumption. We design a character-level encoding strategy for URIs and employ both convolutional and recurrent neural networks to develop a unified prediction model. We use real datasets to simulate requests and analyze the characteristics of the collected power consumption series. Extensive experiments demonstrate that our proposed framework can achieve superior prediction performance compared to other popular leading prediction methods.

Significance Level of Factors for Different Airflow Management Configurations of Data Centers

2005 ◽  
Author(s):  
Saurabh Shrivastava ◽  
Bahgat Sammakia ◽  
Madhusudan Iyengar ◽  
Roger Schmidt
Keyword(s):  
Flow Rate ◽  
Thermal Performance ◽  
Data Center ◽  
Data Centers ◽  
Cooling Capacity ◽  
Significance Level ◽  
Ceiling Height ◽  
Finite Volume Approach ◽  
The Individual ◽  
Tile Flow

Data centers are among the highest energy consuming facilities and are projected to continue to increase in their power consumption for the foreseeable future. Due to the increase of computing power and the decrease in available floor space, maintaining the reliability of the electronic equipment in data centers is a big thermal challenge and, cannot be achieved solely by increasing the cooling capacity of the room. The overall thermal performance of data centers is highly dependent upon the thermal architecture of the facility. This paper presents numerical results of a parametric study, carried out for seven, fairly common, candidate configurations available for the air ducting design for data centers. Among the many factors associated with the data center thermal performance, three main factors at different levels have been selected to characterize their effect. The factors studied are ceiling height, tile flow rate and the location of the return vents. The numerical modeling is performed using a commercially available computational fluid dynamics (CFD) code based on the finite volume approach. This study also includes a summary of the statistical analysis carried out on the data obtained from the numerical parametric analysis, to determine the significance level of each of the individual factors and their interactions, on the thermal performance of the data center. The approach used here is to take an Analysis of Variance (ANOVA) approach, as a tool for determining the significance level of the different variables that affect the overall data center thermal performance. The tile flow rate is found to have significant effect on the thermal performance of all data center configurations studied.

Differentiated Bandwidth Guarantees for Cloud Data Centers

2013 ◽  
Vol 14 (03) ◽  
pp. 1360002
Author(s):  
YANGYANG LI ◽  
HONGBO WANG ◽  
JIANKANG DONG ◽  
JUNBO LI ◽  
SHIDUAN CHENG
Keyword(s):  
Data Center ◽  
Network Performance ◽  
Data Centers ◽  
Service Differentiation ◽  
Nsga Ii ◽  
Network Resource ◽  
Cloud Data ◽  
Fine Grained ◽  
Cloud Data Centers ◽  
Bandwidth Guarantees

By means of virtualization, computing and storage resources are effectively multiplexed by different applications in cloud data centers. However, there lacks useful approaches to share the internal network resource of cloud data centers. Invalid network sharing not only degrade the performance of applications, but also affect the efficiency of data center operation. To guarantee network performance of applications and provide fine-grained service differentiation, in this paper, we propose a differentiated bandwidth guarantee scheme for data center networks. Utility functions are constructed according to the throughput and delay sensitive characteristics of different applications. Aiming to maximize the utility of all applications, the problem is formulated as a multi-objective optimization problem. We solve this problem using a heuristic algorithm: the elitist Non-Dominated Sorted Genetic Algorithm-II(NSGA-II), and we make a multi-attribute decision to refine the solutions. Extensive simulations are conducted to show that our scheme provides minimum band-width guarantees and achieves more fine-grained service differentiation than existing approaches. The simulation also verifies that the proposed mechanism is suitable for arbitrary data center architectures.

Study of CFD-Based Raised-Floor Data Center Cooling With Parametric CRAC Turbofan Blower Airflow Patterns

2021 ◽  
Author(s):  
Zhihang Song ◽  
Wan Chen
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Air Cooling ◽  
Flow Conditions ◽  
Cooling Effectiveness ◽  
Cooling Performance ◽  
Data Center Cooling ◽  
Computational Fluid Dynamics Cfd ◽  
Tile Flow

Abstract Commonly encountered thermal management challenges of today’s rapidly changing power density, raised-floor hot/cold aisle data centers include typically uncontrollable tile flow non-uniformity along the above-floor cold aisle. For example, the operational cooling provision intensity near the Computer Room Airflow Conditioner (CRAC) unit can be far less than that on the other side (far away from the CRAC unit). This undesired trend leads to an unbalanced aisle-level air cooling and subsequent inefficient power consumption. In this study, the CRAC turbofan blower flow boundary conditions were thoroughly investigated. Computational Fluid Dynamics (CFD) based simulations were employed to describe and evaluate the differently configured CRAC turbofan blower flow conditions (i.e., normal, angled, and sheared CRAC flow patterns) as well as their impacts upon the air cooling performance. This work indicates that the considered turbofan blower boundary condition, together with their underlying transportation mechanism within the plenum, might contribute an essential influence to the flow structure adjacent to the tile perforations. In particular, it was found that the sheared CRAC turbofan blower airflow pattern is capable of giving rise to favorable tile flow straightening manners. This finding further promotes an improvement of the consequently obtained aisle-level air cooling effectiveness and efficiencies, contributing to more advanced data center thermal management in the future.

Measured-Temperature Interpolation and Visualization for Data Centers

2013 ◽  
Author(s):  
Xuanhang (Simon) Zhang ◽  
Christopher M. Healey ◽  
Zachary R. Sheffer ◽  
James W. VanGilder
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Three Dimensional ◽  
Measurement Data ◽  
Temperature Sensors ◽  
Sensor Data ◽  
Temperature Fields ◽  
Measured Temperature ◽  
Local Cooling ◽  
Maintenance Requirements

The growing demand for data center facilities has made intelligently managed data center operations necessary. For temperature measurement and thermal management, a common practice is to install a limited number of temperature sensors evenly distributed throughout the room. However, data center operators rarely fully equip facilities with temperature sensors due to their cost, complexity, and maintenance requirements, creating vacancies in the data center temperature and cooling picture. The local nature of sensor data can also be misinterpreted and misused. Without novel methods to interpret and visualize temperatures obtained by prediction or measurement, data center operators cannot easily identify urgent local cooling issues or quickly examine the temperature at other location. This paper presents methods to predict a full three-dimensional temperature field in data centers from a limited number of measurement points. Several different statistical interpolating schemes are discussed. We also validate the interpolated temperature fields against benchmark data from Computation Fluid Dynamics (CFD) and show good agreement.

Data Center Equipment Reliability Concerns—Contamination Issues, Standards Actions, and Case Studies

2013 ◽  
Author(s):  
Chris Muller ◽  
Chuck Arent ◽  
Henry Yu
Keyword(s):  
Case Studies ◽  
Data Center ◽  
Data Centers ◽  
Electronic Equipment ◽  
Circuit Board ◽  
Lead Free ◽  
Reliable Operation ◽  
Contamination Assessment ◽  
Equipment Reliability ◽  
Equipment Failures

Abstract Lead-free manufacturing regulations, reduction in circuit board feature sizes and the miniaturization of components to improve hardware performance have combined to make data center IT equipment more prone to attack by corrosive contaminants. Manufacturers are under pressure to control contamination in the data center environment and maintaining acceptable limits is now critical to the continued reliable operation of datacom and IT equipment. This paper will discuss ongoing reliability issues with electronic equipment in data centers and will present updates on ongoing contamination concerns, standards activities, and case studies from several different locations illustrating the successful application of contamination assessment, control, and monitoring programs to eliminate electronic equipment failures.

scholarly journals Is This a Geolibrary? A Case of the Idaho Geospatial Data Center

2017 ◽  
Vol 19 (1) ◽  
pp. 4-10 ◽  
Author(s):  
Maria Anna Jankowska ◽  
Piotr Jankowski
Keyword(s):  
Digital Library ◽  
Future Development ◽  
Data Center ◽  
Data Centers ◽  
Public Domain ◽  
The State ◽  
Geospatial Data ◽  
Design And Implementation ◽  
Geographic Data

The article presents the Idaho Geospatial Data Center (IGDC), a digital library of public-domain geographic data for the state of Idaho. The design and implementation of IGDC are introduced as part of the larger context of a geolibrary model. The article presents methodology and tools used to build IGDC with the focus on a geolibrary map browser. The use of IGDC is evaluated from the perspective of accessa and demand for geographic data. Finally, the article offers recommendations for future development of geospatial data centers.

Perimeter Cooling Unit and Localized Row-Based Cooling Unit Transient Air Flow Effects Modeling and Characterization in Data Centers

2015 ◽  
Author(s):  
Tianyi Gao ◽  
James Geer ◽  
Bahgat G. Sammakia ◽  
Russell Tipton ◽  
Mark Seymour
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Cooling System ◽  
Air Flow ◽  
Cooling Systems ◽  
Dynamic Thermal Management ◽  
Hybrid Cooling ◽  
Cooling Unit ◽  
Cooling Air

Cooling power constitutes a large portion of the total electrical power consumption in data centers. Approximately 25%∼40% of the electricity used within a production data center is consumed by the cooling system. Improving the cooling energy efficiency has attracted a great deal of research attention. Many strategies have been proposed for cutting the data center energy costs. One of the effective strategies for increasing the cooling efficiency is using dynamic thermal management. Another effective strategy is placing cooling devices (heat exchangers) closer to the source of heat. This is the basic design principle of many hybrid cooling systems and liquid cooling systems for data centers. Dynamic thermal management of data centers is a huge challenge, due to the fact that data centers are operated under complex dynamic conditions, even during normal operating conditions. In addition, hybrid cooling systems for data centers introduce additional localized cooling devices, such as in row cooling units and overhead coolers, which significantly increase the complexity of dynamic thermal management. Therefore, it is of paramount importance to characterize the dynamic responses of data centers under variations from different cooling units, such as cooling air flow rate variations. In this study, a detailed computational analysis of an in row cooler based hybrid cooled data center is conducted using a commercially available computational fluid dynamics (CFD) code. A representative CFD model for a raised floor data center with cold aisle-hot aisle arrangement fashion is developed. The hybrid cooling system is designed using perimeter CRAH units and localized in row cooling units. The CRAH unit supplies centralized cooling air to the under floor plenum, and the cooling air enters the cold aisle through perforated tiles. The in row cooling unit is located on the raised floor between the server racks. It supplies the cooling air directly to the cold aisle, and intakes hot air from the back of the racks (hot aisle). Therefore, two different cooling air sources are supplied to the cold aisle, but the ways they are delivered to the cold aisle are different. Several modeling cases are designed to study the transient effects of variations in the flow rates of the two cooling air sources. The server power and the cooling air flow variation combination scenarios are also modeled and studied. The detailed impacts of each modeling case on the rack inlet air temperature and cold aisle air flow distribution are studied. The results presented in this work provide an understanding of the effects of air flow variations on the thermal performance of data centers. The results and corresponding analysis is used for improving the running efficiency of this type of raised floor hybrid data centers using CRAH and IRC units.

Exergy Analysis of Data Center Thermal Management Systems

2003 ◽  
Author(s):  
Amip J. Shah ◽  
Van P. Carey ◽  
Cullen E. Bash ◽  
Chandrakant D. Patel
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Exergy Analysis ◽  
Thermal Control ◽  
Management Systems ◽  
World Systems ◽  
Sample Data ◽  
Potential Applications ◽  
Temperature Ranges

Data centers today contain more computing and networking equipment than ever before. As a result, a higher amount of cooling is required to maintain facilities within operable temperature ranges. Increasing amounts of resources are spent to achieve thermal control, and tremendous potential benefit lies in the optimization of the cooling process. This paper describes a study performed on data center thermal management systems using the thermodynamic concept of exergy. Specifically, an exergy analysis has been performed on sample data centers in an attempt to identify local and overall inefficiencies within thermal management systems. The development of a model using finite volume analysis has been described, and potential applications to real-world systems have been illustrated. Preliminary results suggest that such an exergy-based analysis can be a useful tool in the design and enhancement of thermal management systems.

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