scholarly journals Design analysis and Work load characteristics of a Micro data Center

2021 ◽  
Vol 850 (1) ◽  
pp. 012018
Author(s):  
T Renugadevi ◽  
D Hari Prasanth ◽  
Appili Yaswanth ◽  
K Muthukumar ◽  
M Venkatesan
Keyword(s):  
Data Storage ◽  
Data Center ◽  
Large Scale ◽  
Data Centers ◽  
Work Load ◽  
Micro Data ◽  
Air Gaps ◽  
Cooling Unit ◽  
Cooling Air ◽  
Quantity Of Heat

Abstract Data centers are large-scale data storage and processing systems. It is made up of a number of servers that must be capable of handling large amount of data. As a result, data centers generate a significant quantity of heat, which must be cooled and kept at an optimal temperature to avoid overheating. To address this problem, thermal analysis of the data center is carried out using numerical methods. The CFD model consists of a micro data center, where conjugate heat transfer effects are studied. A micro data center consists of servers aligned with air gaps alternatively and cooling air is passed between the air gaps to remove heat. In the present work, the design of data center rack is made in such a way that the cold air is in close proximity to servers. The temperature and airflow in the data center are estimated using the model. The air gap is optimally designed for the cooling unit. Temperature distribution of various load configurations is studied. The objective of the study is to find a favorable loading configuration of the micro data center for various loads and effectiveness of distribution of load among the servers.

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.

Minimization of Energy Using Heuristic Resource Allocation and Migration for Cloud Computing

2021 ◽  
Vol 12 (1) ◽  
pp. 74-83
Author(s):  
Manjunatha S. ◽  
Suresh L.
Keyword(s):  
Cloud Computing ◽  
Data Center ◽  
Large Scale ◽  
Data Centers ◽  
Service Providers ◽  
Cost Effective ◽  
Cooling Systems ◽  
Operational Costs ◽  
Cloud Computing Service ◽  
And Migration

Data center is a cost-effective infrastructure for storing large volumes of data and hosting large-scale service applications. Cloud computing service providers are rapidly deploying data centers across the world with a huge number of servers and switches. These data centers consume significant amounts of energy, contributing to high operational costs. Thus, optimizing the energy consumption of servers and networks in data centers can reduce operational costs. In a data center, power consumption is mainly due to servers, networking devices, and cooling systems, and an effective energy-saving strategy is to consolidate the computation and communication into a smaller number of servers and network devices and then power off as many unneeded servers and network devices as possible.

Energy-Efficiency in Cloud Data Centers

2013 ◽  
pp. 241-263
Author(s):  
Burak Kantarci ◽  
Hussein T. Mouftah
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Data Center ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Centers ◽  
High Energy ◽  
It Services ◽  
Data Center Network ◽  
Cloud Data

Cloud computing aims to migrate IT services to distant data centers in order to reduce the dependency of the services on the limited local resources. Cloud computing provides access to distant computing resources via Web services while the end user is not aware of how the IT infrastructure is managed. Besides the novelties and advantages of cloud computing, deployment of a large number of servers and data centers introduces the challenge of high energy consumption. Additionally, transportation of IT services over the Internet backbone accumulates the energy consumption problem of the backbone infrastructure. In this chapter, the authors cover energy-efficient cloud computing studies in the data center involving various aspects such as: reduction of processing, storage, and data center network-related power consumption. They first provide a brief overview of the existing approaches on cool data centers that can be mainly grouped as studies on virtualization techniques, energy-efficient data center network design schemes, and studies that monitor the data center thermal activity by Wireless Sensor Networks (WSNs). The authors also present solutions that aim to reduce energy consumption in data centers by considering the communications aspects over the backbone of large-scale cloud systems.

Raised Floor Hybrid Cooled Data Center: Effect on Rack Inlet Air Temperatures When In Row Cooling Units are Installed Between the Racks

2015 ◽  
Author(s):  
Tianyi Gao ◽  
James Geer ◽  
Russell Tipton ◽  
Bruce Murray ◽  
Bahgat G. Sammakia ◽  
...  
Keyword(s):  
Flow Rate ◽  
Data Center ◽  
Heat Load ◽  
Data Centers ◽  
Cooling System ◽  
Air Flow ◽  
Inlet Temperature ◽  
Air Flow Rate ◽  
Air Temperatures ◽  
Cooling Unit

The heat dissipated by high performance IT equipment such as servers and switches in data centers is increasing rapidly, which makes the thermal management even more challenging. IT equipment is typically designed to operate at a rack inlet air temperature ranging between 10 °C and 35 °C. The newest published environmental standards for operating IT equipment proposed by ASHARE specify a long term recommended dry bulb IT air inlet temperature range as 18°C to 27°C. In terms of the short term specification, the largest allowable inlet temperature range to operate at is between 5°C and 45°C. Failure in maintaining these specifications will lead to significantly detrimental impacts to the performance and reliability of these electronic devices. Thus, understanding the cooling system is of paramount importance for the design and operation of data centers. In this paper, a hybrid cooling system is numerically modeled and investigated. The numerical modeling is conducted using a commercial computational fluid dynamics (CFD) code. The hybrid cooling strategy is specified by mounting the in row cooling units between the server racks to assist the raised floor air cooling. The effect of several input variables, including rack heat load and heat density, rack air flow rate, in row cooling unit operating cooling fluid flow rate and temperature, in row coil effectiveness, centralized cooling unit supply air flow rate, non-uniformity in rack heat load, and raised floor height are studied parametrically. Their detailed effects on the rack inlet air temperatures and the in row cooler performance are presented. The modeling results and corresponding analyses are used to develop general installation and operation guidance for the in row cooler strategy of a data center.

scholarly journals Heuristic algorithms for joint optimization of unicast and anycast traffic in elastic optical network–based large–scale computing systems

2017 ◽  
Vol 27 (3) ◽  
pp. 605-622 ◽  
Author(s):  
Marcin Markowski
Keyword(s):  
Optical Networks ◽  
Wavelength Division Multiplexing ◽  
Data Center ◽  
Large Scale ◽  
Data Centers ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Approximate Solutions ◽  
Computing Systems ◽  
Large Scale Computing

AbstractIn recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios.

scholarly journals Increasing Security for Cloud Computing By Steganography in Image Edges

2017 ◽  
Vol 27 (4) ◽  
Author(s):  
Hassan Hadi Saleh
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Security ◽  
Data Center ◽  
Data Centers ◽  
Data Access ◽  
Good Method ◽  
Color Images ◽  
Image Edges ◽  
Fundamental Objective

The security of data storage in “cloud” is big challenge because the data keep within resources that may be accessed by particular machines. The managing of these data and services may not be high reliable. Therefore, the security of data is highly challenging. To increase the security of data in data center of cloud, we have introduced good method to ensure data security in “cloud computing” by methods of data hiding using color images which is called steganography. The fundamental objective of this paper is to prevent "Data Access” by unauthorized or opponent users. This scheme stores data at data centers within edges of color images and retrieves data from it when it is wanted.

scholarly journals Modified Viterbi Algorithm with Feedback Using a Two-Dimensional 3-Way Generalized Partial Response Target for Bit-Patterned Media Recording Systems

2021 ◽  
Vol 11 (2) ◽  
pp. 728
Author(s):  
Thien An Nguyen ◽  
Jaejin Lee
Keyword(s):  
Partial Response ◽  
Data Storage ◽  
Large Scale ◽  
Data Centers ◽  
Viterbi Algorithm ◽  
Storage Systems ◽  
Magnetic Data ◽  
Innovative Technology ◽  
Two Dimensional ◽  
Intertrack Interference

The ever-increasing demand for data in recent times has led to the emergence of big data and cloud data. The growth in these fields has necessitated that data be centrally stored in data centers. To meet the need for large-scale storage systems at data centers, innovative technology such as bit-pattern media recording (BPMR) has been developed. With BPMR technology, we are able to achieve significant improvements in high areal density (AD) of magnetic data storage systems. However, two-dimensional (2D) interference is a common issue faced with high AD. Intersymbol interference and intertrack interference occur when the distance between the islands is decreased in the down-track and cross-track, respectively. 2D interference adversely affects the performance of BPMR. In this paper, we propose an improved modified Viterbi algorithm (MVA) exploiting a feedback and a new 2D three-way form of a generalized partial response (GPR) target. The proposed MVA with feedback is superior to the previous MVA by eliminating intertrack interference (ITI) more effectively. With the three-way GPR target, the proposed algorithm achieves more stable performance compared to the previous detection algorithms for the track misregistration effect.

scholarly journals TCP Incast in Data Center Networks: Issue and Existing Solutions

2019 ◽  
Vol 9 (2) ◽  
pp. 2001-2012
Keyword(s):  
Data Storage ◽  
Data Center ◽  
Web Search ◽  
Data Centers ◽  
Propagation Delay ◽  
Video Data ◽  
Application Layer ◽  
Procedural Approach ◽  
Tcp Protocol ◽  
High Bandwidth

Data centers networks supports heterogeneous kind of applications like social networking, e-commerce, web search, video data hosting, computation-intensive and data-storage. It has high-bandwidth links, low propagation delay and commodity switches with small-size buffers. Under cluster-based storage environment, data center supports barrier-synchronized manyto-one communication pattern where multiple worker nodes simultaneously transmit bulk of data to single aggregator node by running standard TCP protocol. This synchronized transmission may overload aggregator’s switch buffer, which leads to severe packet loss and overall throughput fall. This is called as TCP Incast problem. This paper analyses issue of TCP Incast and provides detailed survey about several solutions at link, transport and application layer to mitigate impact of TCP Incast in data center network. Solutions are described with their procedural approach for alleviating Incast. Comparative evaluation between these solutions provides understanding about their merits, demerits and applicability under various implementation circumstances.

scholarly journals DESIGN AND VERIFICATION OF REMOTE SENSING IMAGE DATA CENTER STORAGE ARCHITECTURE BASED ON HADOOP

2018 ◽  
Vol XLII-3 ◽  
pp. 1639-1642
Author(s):  
D. Tang ◽  
X. Zhou ◽  
Y. Jing ◽  
W. Cong ◽  
C. Li
Keyword(s):  
Remote Sensing ◽  
Data Storage ◽  
Data Center ◽  
High Speed ◽  
Large Scale ◽  
Distributed Storage ◽  
Image Data ◽  
Remotely Sensed Data ◽  
Processing Technologies ◽  
Data Parallel

The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.

scholarly journals The National Data Center and the Federal Information Network: A Paradox

2015 ◽  
Vol 10 ◽  
Author(s):  
Sean Cawley
Keyword(s):  
Data Storage ◽  
Data Center ◽  
Information Transfer ◽  
Data Centers ◽  
New Technologies ◽  
Technological Advancement ◽  
National Data ◽  
Privacy Concerns ◽  
Storage And Retrieval ◽  
Implicit Data

Technological advancement and increasing data collection activities compelled the call for a National Data Center in 1965. Theoretically, the Center would increase efficiency and diminish costs, as the inefficiencies of information transfer between agencies and organizations steadily rose. However, a firestorm of criticism met the proposal from a number of sectors due to a perceived lack of privacy concerns, which eventually spelled the Center's demise. The destruction of an explicit locale for data storage and retrieval, however, catalyzed the formation of numerous implicit data centers that jeopardized privacy to a far greater degree than it was originally feared the Center would. The history of the National Data Center's demise and the subsequent construction of implicit data centers consists of a useful case study when considering the proper reaction to perceived privacy concerns regarding new technologies.

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