Experimental Characterization of Various Cold Aisle Containment Configurations for Data Centers

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Vikneshan Sundaralingam ◽  
Vaibhav K. Arghode ◽  
Yogendra Joshi ◽  
Wally Phelps
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Processing Unit ◽  
Central Processing ◽  
Contour Plots ◽  
Efficient Data ◽  
Use Of The Internet ◽  
The Many ◽  
Cold Aisle Containment

The data center industry has experienced significant growth over the last decade, mainly due to the increased use of the internet for our day to day activities such as e-commerce, social media, video streaming, and healthcare. This growth in demand results in higher energy costs, as data centers can be energy intensive facilities. A significant portion of the energy used in data centers is for cooling purposes. Hence, it is one of the important areas of optimization to be addressed to create more efficient data centers. Among the many ways to increase data center efficiencies, air flow management is a key solution to many existing data centers. Fundamentally, there are three main schemes: hot-aisle containment, cold-aisle containment, and exhaust chimney containment. This paper's focus is to experimentally characterize the following cold aisle configurations: open aisle, partially contained aisle, and fully contained aisles. Experimental data presented to evaluate the effectiveness of the different configurations are rack inlet contour plots, tile and rack flow rates, pressure measurements, and server central processing unit (CPU) temperatures.

Dynamic Load Balancing Using Actual Workload Traces Based on Central Processing Unit Temperatures

2019 ◽  
Vol 141 (3) ◽  
Author(s):  
Yusuke Nakajo ◽  
Jayati Athavale ◽  
Minami Yoda ◽  
Yogendra Joshi ◽  
Hiroaki Nishi
Keyword(s):  
Load Balancing ◽  
Dynamic Load ◽  
Data Centers ◽  
Web Applications ◽  
Experimental Studies ◽  
Central Processing Unit ◽  
Dynamic Load Balancing ◽  
Processing Unit ◽  
Central Processing ◽  
Processing Times

Abstract With the rapid growth in demand for distributed computing, data centers are a critical physical component of the “cloud.” Recent studies show that the energy consumption of data centers for both cooling and computing keeps increasing, and the growth in server power densities makes it ever more challenging to keep the servers below their maximum operating temperature. This paper presents a new dynamic load-balancing approach based on individual server central processing unit (CPU) temperatures. In this approach, a load balancer assigns a task in real time to a server based on the objective to keep the CPU temperatures below a maximum value. Experimental studies are conducted in a single rack based on production workload traces of Google clusters. This study also compares the performance of this method with two other load balancing approaches, Round Robin, and a CPU utilization-based method in terms of temperature distributions, local fan rotation speeds, system loads, and server processing times. Furthermore, we investigate how the effect of the proposed load balancing changes with different assumed applications run on servers. The results indicate that this new method can more effectively reduce both server CPU temperatures and local fan rotation speed in a rack especially for the most of web applications.

Load Capacity and Thermal Efficiency Optimization of a Research Data Center Using Computational Modeling

2015 ◽  
Author(s):  
Joseph R. H. Schaadt ◽  
Kamran Fouladi ◽  
Aaron P. Wemhoff ◽  
Joseph G. Pigeon
Keyword(s):  
Flow Rate ◽  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Load Capacity ◽  
Research Data ◽  
Optimal Operating ◽  
Cold Aisle Containment ◽  
Operating Points ◽  
The Ideal

Data centers are most commonly cooled by air delivered to electronic equipment from centralized cooling systems. The research presented here is motivated by the need for strategies to improve and optimize the load capacity and thermal efficiency of data centers by using computational fluid dynamics (CFD). Here, CFD is used to model and optimize the Villanova Steel Orca Research Center (VSORC). VSORC, presently in the design stages, will provide a testing environment as well as the capability to investigate best practices and state of the art strategies including hybrid cooling, IT load distribution, density zones, and hot aisle and cold aisle containment. The results of this study will be used in the overall design and construction of the aforementioned research data center. The objective of this study is to find the optimal operating points and design layout of a data center while still meeting certain design constraints. A focus is on finding both the ideal total supply flow rate of the air conditioning units and the ideal chilled water supply temperature (CHWST) setpoint under different data center design configurations and load capacities. The total supply flow rate of the air conditioning units and the supply temperature setpoint of the chilled water system are varied as design parameters in order to systematically determine the optimal operating points. The study also examines the influence of hot aisle and cold aisle containment strategies in full containment, half containment, and no containment configurations on the determined optimal operating conditions for the modeled research data center.

Development and Experimental Validation of an Exergy-Based Computational Tool for Data Center Thermal Management

Volume 1 ◽  
2004 ◽  
Author(s):  
Amip J. Shah ◽  
Van P. Carey ◽  
Cullen E. Bash ◽  
Chandrakant D. Patel
Keyword(s):  
Thermal Management ◽  
Data Center ◽  
Data Centers ◽  
Second Law Of Thermodynamics ◽  
Computational Tool ◽  
Future Data ◽  
Efficient Data ◽  
Management Techniques ◽  
Power Densities ◽  
Further Development

The recent miniaturization of electronic devices and compaction of computer systems will soon lead to data centers with power densities of the order of 300 W/ft2. At these levels, traditional thermal management techniques are unlikely to suffice. To enable the dynamic smart cooling systems necessary for future data centers, an exergetic approach based on the second law of thermodynamics has recently been proposed. However, no experimental data related to this concept is currently available. This paper discusses the development and subsequent validation of an exergy-based computer model at an instrumented data center in Palo Alto, California. The study finds that when appropriately calibrated, such a computational tool can successfully predict information about local and global thermal performance that cannot be perceived intuitively from traditional design methods. Further development of the concept has promising potential for efficient data center thermal management.

scholarly journals Virtual CPU Scaling for Efficient Server Power Consumption in Cloud Data Center

2020 ◽  
Vol 3 (2) ◽  
pp. 11-20
Author(s):  
Noora N. Bhaya ◽  
Rabah A. Ahmed
Keyword(s):  
Cloud Computing ◽  
Power Efficiency ◽  
Data Centers ◽  
Power Saving ◽  
Processing Unit ◽  
Cloud Infrastructure ◽  
Financial Benefit ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Central Processing

Cloud computing is a fast-growing technology used by major corporations these days because of the flexibility framework it provides to consumers. Cloud technology requires large data centers consisting of multiple IT equipment and servers. One main problem with these data centers is the vast amount of power consumed during servers operation. This reduces financial benefit and increases the need to produce more energy to cover the needs of operating the cloud infrastructure. This paper proposes an approach for managing the virtual central processing unit (vCPU) of a virtual machine to improve server power efficiency. A framework is used to study the proposed approach while processing different types of workloads widely found in most general-purpose cloud computing applications. Results indicate an improvement in server power saving.

Green Energy in Data Centers Using Internet of Things

2021 ◽  
pp. 225-246
Author(s):  
Vasaki Ponnusamy ◽  
Bobby Sharma ◽  
Gan Ming Lee
Keyword(s):  
Cloud Computing ◽  
Power Management ◽  
Data Center ◽  
Data Centers ◽  
High Capacity ◽  
Green Energy ◽  
Cooling Systems ◽  
Efficient Data ◽  
Green Data Center ◽  
Increasing Demand

Green energy infrastructure with the internet technologies relies on five important domains: green machine to machine (M2M), green cloud computing (CC), green data center (DC), green ICT, and green cellular. The ever-increasing demand for cloud computing and heavy dependence on cloud for storage, processing, and applications results in the need for more data centers with high capacity. Power management using wireless sensor networks (WSN) can be a potential solution as there has been a lot of works suing WSN for power management for green buildings, green home, and green farming. The same design can be applied to data centers with modifications to cater for data centers. Since WSN is part of IoT, various IoT-related solutions can be proposed for green data center solutions. A hybrid model that consists of virtualization, cooling systems, and IoT shows energy efficient data center designs. There have been various efforts as such, and this research will present green energy designs and mainly IoT-related initiatives for green-aware data centers.

scholarly journals B3: Fuzzy-Based Data Center Load Optimization in Cloud Computing

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
M. Jaiganesh ◽  
A. Vincent Antony Kumar
Keyword(s):  
Cloud Computing ◽  
Data Center ◽  
Large Data ◽  
Service Level ◽  
Processing Unit ◽  
High Definition ◽  
Load Optimization ◽  
Central Processing ◽  
Order Of Magnitude ◽  
Internet Connections

Cloud computing started a new era in getting variety of information puddles through various internet connections by any connective devices. It provides pay and use method for grasping the services by the clients. Data center is a sophisticated high definition server, which runs applications virtually in cloud computing. It moves the application, services, and data to a large data center. Data center provides more service level, which covers maximum of users. In order to find the overall load efficiency, the utilization service in data center is a definite task. Hence, we propose a novel method to find the efficiency of the data center in cloud computing. The goal is to optimize date center utilization in terms of three big factors—Bandwidth, Memory, and Central Processing Unit (CPU) cycle. We constructed a fuzzy expert system model to obtain maximum Data Center Load Efficiency (DCLE) in cloud computing environments. The advantage of the proposed system lies in DCLE computing. While computing, it allows regular evaluation of services to any number of clients. This approach indicates that the current cloud needs an order of magnitude in data center management to be used in next generation computing.

scholarly journals IoT Based Air Quality Monitoring System

2021 ◽  
pp. 1106-1114
Author(s):  
Mr. Nitin V. Bansod ◽  
Prof. U.W. Hore
Keyword(s):  
Monitoring System ◽  
Data Center ◽  
Web Gis ◽  
Processing Unit ◽  
Gps Receiver ◽  
Monitoring Equipment ◽  
Web Mapping ◽  
Central Processing ◽  
Sensors Array ◽  
Receiver Module

A remote online carbon dioxide (CO2) concentration monitoring system is developed, based on the technologies of wireless sensor networks, in allusion to the gas leakage monitoring requirement for CO2 capture and storage. The remote online CO2 monitoring system consists of monitoring equipment, a data center server, and the clients. The monitoring equipment is composed of a central processing unit (CPU), air environment sensors array, global positioning system (GPS) receiver module, secure digital memory card (SD) storage module, liquid crystal display (LCD) module, and general packet radio service (GPRS) wireless transmission module. The sensors array of CO2, temperature, humidity, and light intensity are used to collect data and the GPS receiver module is adopted to collect location and time information. The CPU automatically stores the collected data in the server and displays them on the LCD display module in real-time. Afterwards, the GPRS module continuously wirelessly transmits the collected information to the data center server. The online monitoring Web GIS clients are developed using a PHP programming language, which runs on the Apache web server. MySQL is utilized as the database because of its speed and reliability, and the stunning cross browser web maps are created, optimized, and deployed with the Open Layers JavaScript web-mapping library.

scholarly journals Air Quality Monitoring Using Internet of Things

2021 ◽  
pp. 208-214
Author(s):  
Mr. Nitin V. Bansod ◽  
Prof. U. V. Hore
Keyword(s):  
Monitoring System ◽  
Data Center ◽  
Web Gis ◽  
Processing Unit ◽  
Gps Receiver ◽  
Monitoring Equipment ◽  
Display Module ◽  
Central Processing ◽  
Sensors Array ◽  
Receiver Module

A remote online carbon dioxide (CO2) concentration monitoring system is developed, based on the technologies of wireless sensor networks, in allusion to the gas leakage monitoring requirement for CO2 capture and storage. The remote online CO2 monitoring system consists of monitoring equipment, a data center server, and the clients. The monitoring equipment is composed of a central processing unit (CPU), air environment sensors array, global positioning system (GPS) receiver module, secure digital memory card (SD) storage module, liquid crystal display (LCD) module, and general packet radio service (GPRS) wireless transmission module. The sensors array of CO2, temperature, humidity, and light intensity are used to collect data and the GPS receiver module is adopted to collect location and time information. The CPU automatically stores the collected data in the server and displays them on the LCD display module in real-time. Afterwards, the GPRS module continuously wirelessly transmits the collected information to the data center server. The online monitoring Web GIS clients are developed using a PHP programming language, which runs on the Apache web server. MySQL is utilized as the database because of its speed and reliability, and the stunning cross browser web maps are created, optimized, and deployed with the Open Layers JavaScript webmapping library.

scholarly journals New voltage and temperature scalable gate delay model applied to a 14nm technology

2020 ◽  
Vol 20 (3) ◽  
pp. 1210
Author(s):  
Kenza Charafeddine ◽  
Faissal Ouardi
Keyword(s):  
Classical Method ◽  
Processing Unit ◽  
Gate Delay ◽  
Standard Cell ◽  
Delay Model ◽  
Standard Cell Library ◽  
Central Processing ◽  
Cell Library ◽  
Standard Cells

<p>The following work shows an innovative approach to model the timing of<br />standard cells. By using mathematical models instead of the classical SPICE-based characterization, a high amount of CPU (Central Processing Unit) cores is saved and less amount of data is stored. In the present work,<br />characterization of cells of a standard cell library is done in an hour whereas<br />it is done in 650 hours with the classical method. Also, a method for<br />validating and verification of the precision of the modelled data is presented<br />by comparing them on a implemented circuit. The output of implementations shows less than 3% of error between the two methods.</p>

Energy Savings Through Hot and Cold Aisle Containment Configurations for Air Cooled Servers in Data Centers

2011 ◽  
Author(s):  
Roger Schmidt ◽  
Aparna Vallury ◽  
Madhusudan Iyengar
Keyword(s):  
Energy Efficiency ◽  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Energy Savings ◽  
Green Technologies ◽  
Advantages And Disadvantages ◽  
Hot Air ◽  
Type Data ◽  
Cold Aisle Containment

The increased focus on green technologies and energy efficiency coupled with the insatiable desire of IT equipment customers for more performance has driven manufacturers to deploy energy efficient technologies in the data centers. This paper describes a technique to achieve significant energy savings by preventing the cold and hot air streams within the data center from mixing. More specifically, techniques will be described that will separate the cool supply air to the server racks and exhaust hot air that returns to the air conditioning units. This separation can be achieved by three types of containment systems — cold aisle containment, hot aisle containment, and server rack exhaust chimneys. The advantages and disadvantages of each technique will be outlined. To show the potential for energy efficiency improvements a case study in deploying a cold aisle containment solution for a 8944 ft2 data center will be presented. This study will show that 59% of the energy required for the computer room air conditioning (CRAC) units used in a traditional open type data center could be saved.

Sign in / Sign up

Export Citation Format

Share Document