towards green computing application for measuring the sustainability of data centers: an analytical...

Towards Green Computing Application for Measuring the Sustainability of Data

Centers: an Analytical Survey

Zohreh Gandomi and Salmiah Binti Amin

Asia Pacific University of Technology and Innovation

Kuala Lumpur, Malaysia

[email protected], [email protected]

ABSTRACT

Green computing is a new term which is defined to

make computing systems such as data centers more

energy efficient. Using various methods to prepare a

green networks and help CO2 reduction has been a

major issue for climate change in recent years. This

research work is designed to help admins to make a

green data centers by using an analytical survey and

new tool. The results in this research shows making

data centers green is a major concern for data

admins, however some of them have limited

information about the energy efficiency methods.

Finally, Green Data Center (GDC), use case design

and graphical user interface recommended for

future works in order to assist network

administrators to make their data centers green.

This research expected to provide analytical survey

towards green computing application for measuring

the sustainability of data centers.

KEYWORDS

Data centers; green metrics; energy efficiency;

power usage effectiveness; green networks.

1 INTRODUCTION

In recent years green computing term is

defined to make computer systems such as data

centers more efficient and more

environmentally friendly. In order to evaluate

the green index of data centers, some green

metrics such as Power Usage Effectiveness

(PUE) and Data Center infrastructure

Efficiency (DCIE) are defined. Power

consumption measurement and calculation of

energy cost and carbon footprint are extra

features that can assist data center

administrators to monitor the energy usage.

Figure 1 demonstrates the numbers of

published papers in green computing during 20

years based on ISI web of science. This

information is essential for showing the

importance of green computing and fast

increase in number of its publications.

Figure 1. The numbers of published papers in Green

Computing during 20 years [1].

In this research, as a first part, the

comprehensive questionnaire survey is done

about the application of green metric in data

centers and knowledge of data center admins

regarding green metrics. After that, a Green

Data Center (GDC) tool is designed using use

case diagram and graphical user interface

diagram recommended to monitor PUE and

DCIE of data centers. This GDC tool expected

to monitor PUE and DCIE and calculate annual

power consumption, energy cost and carbon

footprint of data centers.

ISBN: 978-1-941968-02-4 ©2014 SDIWC 86

Proceedings of the International Conference on Electrical, Electronics, Computer Engineering and their Applications, Kuala Lumpur, Malaysia, 2014

mailto:[email protected]

Figure below shows the analysis and

definition of PUE according to Intel report.

Figure 2. PUE Values and Analysis [2].

On the other side, various objectives are

considered for this study to achieve the

mentioned aims as follows:

To propose a new tool to make data centers more energy efficient.

To propose a new tool that expected to measure the energy usage, cost of energy

and carbon footprint of data centers.

To propose a new tool that expected to

monitor green metrics of data centers such

as PUE and DCIE for level of energy

efficiency.

2 RESEARCH STATEMENT

Many authors in recent years discussed

about the green computing. One of the main

aims of green computing has been reducing the

energy usage and CO2 emission. In case of measuring power consumption in data centers

and energy efficiency, there are two metrics

that are widely used in network infrastructure.

Power Usage Effectiveness (PUE) and Data

Center Infrastructure Efficiency (DCIE) are

these two metrics. Moreover, PUE and DCIE

are using to optimize energy by implement

some techniques to make green data centers [3].

In the next section, formula for calculating

PUE, DCIE, electricity used per year, annual

power cost and carbon footprint is presented

with comprehensive explanation.

The first step to measure green metrics for

data centers is estimation of energy or power

consumption for each device in data center.

After calculation of IT and facility load per

hour, the total energy consumption in data

centers will be calculated. Measurement of cost

of energy, total energy consumption and carbon

footprint is done by developed tool in this

research.

This research work has had some parts. The

first part investigates about the green metrics of

data centers and proposes the new technique in

order to maximize the energy efficiency.

The next part is about using C# and XML

programming language to develop a tool in

order to monitor energy efficiency in data

centers. This part of research is defined as

challengeable and novel section of this

research.

2.1 Carbon Footprint in Data Centers

Reducing the CO2 emission has to be

considered in two different parts:

1) Design of Network Elements

The green design is assumed as a major

concern in new technologies. Various devices

and design strategies in recent years have

considered the green elements in data centers.

In green network design, a telnet protocol can

help to sleep clients after a given time and reuse

later [4]. For instance a green LAN Switch can

be helpful to save energy compare to other

models. Figure below shows the Cisco Catalyst

2960-X switches which Cisco recently designed

as the next generation of switches.

2) Operation Part by Reducing Energy

Consumption

By regarding contribution of each device in

energy consumption in data centers, developer

can focus on main devices for saving energy.

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As shown in Figure below, each element has its

own percentage in energy usage in a data

center.

Figure 3. A Green LAN Switch Designed by Cisco [5].

As illustrated in figure below, LAN

switches with 53.7% have the highest amount

of energy consumption or electricity usage.

Therefore, implementing a technique for

calculating and monitoring carbon footprint that

is related to data centers is considered as a

method in this research.

Figure 4. Contribution of Various Network Devices in

Energy Consumption [6].

2.2 Estimated Electricity Usage in APU Data

Center

One of major problem in data centers is

high cost of consumed power due to increasing

energy usage. More energy usage of network

infrastructures has more cost. Recently, Cisco

faced a high cost issue for the network

infrastructures [6].

Based on research on data center [7] power

consumption of one server is between 500 to

1,200 watts per hour. Therefore 850 watts per

hour is the average of electricity usage for one

server. Therefore by turning off some of the

equipment during off peak hours, this amount

will be decreased [8]. Moreover, by decreasing

this amount of energy usage the cost will be

lower [9]. Table below shows the power

consumption for estimated facilities in data

centers.

Table 1. Equipment and Average Cost of Energy for

Some Facilities in Data Center.

Main Equipment Unit Load per Hour /

kWh

Unit Cost of

Energy

(kWh/RM)

Server 0.85 0.33

Router 0.42 0.33

Switch 0.14 0.39

Cooling System 3.5 0.33

Lighting System 0.02 0.33

3 METHODOLOGY

3.1 Calculating PUE and DCIE

1) Power Usage Effectiveness (PUE)

In data centers PUE is defined as Power

Usage Effectiveness as one of the main metrics for energy efficiency. The formula for calculating PUE is shown in equation below [10]:

PUE = Total Facility Load/Total IT Load (1)

In this equation total facility load is overall

electricity usage by all equipment in data center

such as lighting, servers, cooling system and

routers. Moreover, total IT load is whole power

consumption of IT equipment such as servers,

routers and switches in data center. This metric

is helpful for understanding the level of

efficiency for data centers. The PUE amount

from 1.2 to 2.0 in data centers is considered as

efficient level. For instance the value of 3.0 for

PUE means that power usage of all facilities in

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data center is three times greater than energy

usage of IT equipment [11].

2) Data Center Infrastructure Efficiency

(DCIE).

Another metric which indicate the level of

efficiency in data centers is Data Center

Infrastructure Efficiency or DCIE. In IT

industry DCIE is calculated as below [12]:

DCIE = (Total IT Load/Total Facility Load) x

100 (2)

This efficiency metric is useful to measure

the performance of green data centers and

demonstrate the percentage of efficiency level.

Furthermore, it represents a reverse value of

PUE multiply by 100. For instance the value of

33% for DCIE metric, demonstrate that the

level of efficiency in data center is very

inefficient [13].

3.2 Quantitative Research

In terms of research methods, there are two

types of quantitative and qualitative methods.

In this research quantitative research method is

discussed. This method can be helpful to

provide large, representative samples of desired

information [14].

For data collection, the primary source in

this research is assumed to be based on survey

questionnaire of Green Data Centers. This task

is done by giving questionnaire to network

administrators about green networking in data

centers infrastructures and collect information

by their answers. This material is about number

of servers, energy consumption of equipment in

data centers, green metrics, etc.

Questions for this survey are designed in

three different parts to conclude desired result.

1) Part 1

In this section the objective of five

questions is to know what network

administrators think about importance of

energy efficiency and CO2 emission in data

centers.

The finding of this part is considered to be

the level of knowledge of data administrators

about energy efficiency, CO2 emission and

electricity usage in data centers and how much

these factors are significant.

2) Part 2

The objective of information gathering from

questions number 6, 7, 8 and 9 is that how

many servers the specific data center has. Also

network administrator is asked about metrics

and tools to save power in data centers and

make data center greener.

The result of these questions is how large

the exact data center is. Moreover, the fact that

how much information the network

administrator of data center has about metrics

and tools for saving power is the main finding

of this part.

3) Part 3

The principal aim of questions number 10

to 15 is collect information that how much

network administrators are enthusiast about

Green Network and energy efficiency in data

centers.

As main conclusion of these six questions is

interest level of managers and network

administrators to use Green Grid in their data

centers. Moreover it is examined that weather

network administrators are ready to pay extra

cost to make their data centers Green or not.

4 RESULTS AND DISCUSSION

The internet based questionnaire has filled

up by 15 network administrator through online

form. The questions sent by email to more than

20 network administrators and 15 results

achieved. The paper based questionnaire is

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done by other three data administrators. The

results are discuses as follows:

1) Data Centers are a major part in IT

industry.

Figure 5. Analysis of Question 1.

Based on the results for first question, it

shows that majority of data administrators

believe data centers are one of major part in IT

industry. Definitely this fact is important in

future research about energy consumption in

data centers.

2) Electricity usage in data centers is very

high.


Almost all of data center admins are agree

or strongly agree that this major part of IT

industry (data center) is using high amount of

energy due to large numbers of electricity

devices. Until this question everything shows

the importance of energy efficiency research

about data centers.

3) A solution for energy efficiency is a

must for networks.


Although around 26% of admins are not

sure about the importance of energy efficiency

as a solution for data centers, however 73% of

them know about the effectiveness of this

solution. The 26% of admins need education

and information about energy efficiency.

4) The effective tool for energy and

electricity calculation in data centers

will be so useful.


This part of analysis shows a new and

interesting result. Although in question number

3, 73% of admins know the importance of

energy efficiency for data centers, however

80% of them need a tool. A tool for calculation

of energy and electricity in data centers can

help them to understand the importance of

energy efficiency. Therefore, first they need to

know the level of usage and then understand the

importance of decreasing this level.

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5) CO2 emission in data centers is

increasing.


The analysis shows 73% of admins know

the CO2 emission in data centers is increasing

but still 27% of them uncertain and disagree on

that. This shows the importance of having

Green Data Centers proposed in this research to

cater the increasing amount of CO2 emission in

data centers.

6) How much is top management of your

DC concerned about the “Green Data

Centers”?


This part of results can show a good sign

for concern of top management about green

data centers. It seems that 86% of top

management who are the decision makers has

some knowledge about the green data centers.

7) How many servers do you have in your

data center?


The number of servers is important in

energy calculation of data centers. As proved,

majority of data centers are using less than 100

servers.

8) You are familiar with which one of the

following power solution techniques in

data centers?


Green metrics is the most familiar power

solution technique in data centers among

admins. 46 % of them are familiar with green

metrics and power management tool the second

one.

9) Does your data center apply any power

consumption tools?

This result is the main reason for our

research. Most of admins knows the importance

of energy efficiency, usage of energy

consumption tool and green data centers,

however currently 71% of them do not have

any power consumption tools.

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10) Does your data center use any metric to

measure energy consumption at this

time?


Moreover, metrics are important but admins

do not use any metric to measure energy

consumption in their data centers. Therefore,

there is a lack of power consumption tools and

metrics.

11) What is the PUE of facilities in your

data center?

14% of admins in data centers are not

familiar with PUE. The amount of PUE in

about 28% of data centers are so high and in

29% is medium. Therefore for 57% of data

centers we need to work on their metrics to

make a greener network.


12) What is the percentage of DCIE in your

data center?


21% of admins do not have idea about the

DCIE percentage. The 50 % of data centers has

less than 50 percentage DCIE which is not

good. This question same as previous one show

that we need to work on their metrics to make a

greener network.

13) Which one has a key role in energy

efficiency in your data center?


40% of admins are thinking that role of

cooling systems is important in energy

efficiency of data centers. The other 53%

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believe that energy efficient method for servers

is more important.

14) Have you taken any step to make your

data center green?


This question presents that 62% of data

centers are without any action to make their

data centers green. The other 38% can be

considered as green or partially green data

centers.

15) What factors motivated you to use

software for energy consumption?


It seems that two major terms for admins to

make a motivation for them for green data

centers are cost and green network. Cost is a

concern for 37% of admins and having a green

network is a concern for 30%. Reduction of

CO2 emission and energy efficiency are less

important factors among admins.

5 PROPOSED SOLUTION: GDC TOOL

In this research, Green Data Center (GDC)

tool is defined as a proper tool for data centers

that can be develop in future. This software is

according to the results of previous

questionaries’ survey and shows the importance

of green metrics monitoring such as PUE and

DCIE. Moreover, Green metrics are considered

as important factors in power efficiency and

power consumption of data centers in this tool.

Power consumption calculation can be defined

in this software as an essential item for decision

makers to implement green networks. As one of

the metrics, power usage effectiveness (PUE) is

a factor to find that energy efficiency is

considered in data centers or not. Moreover,

PUE is a metric to measure of how much power

is used by equipment is data centers.

5.1 Justification of Using Two Programming

Languages

In order to choose proper languages for

developing the proposed software, below

comparisons between C++, Java and C# have

been done in the following.

1) Comparison of C# and C++

The comparison of two programming languages

such as C# and C++ are indicating in table 2

below.

2) Comparison of C# and Java

Table 3 below shows 5 different

comparisons of C# and Java programming

Languages.

3) Comparison of XML and HTML

Different assessment between XML and

HTML are shown in table 4 below.

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Table 2. Comparison of C# and C++.

C# C++

Library

Has a more

complete

standard library

Simple Library

Features

Has useful

features like

cleaner syntax

Not complete

Security Data is more

secured

Security Level

is Less than

Language

Type

Multi paradigm

programming

language

General

purpose

programming

language

Operating

System

Windows, Linux

and Mac OS X Only Windows

Table 3. Comparison of C# and Java.

C# Java

Complex

Numbers Yes No

Object

Initializers Yes No

Implicit

Conversions Yes No

Pointer Yes No

Enumeration

Type Implicitly Class

Table 4. Comparison of XML and HTML

XML HTML

Type Dynamic Static

Usage

To develop

markup

languages

Display a web

page.

Tags Create by user Predefined

Design

With focus on

storing and

transporting

data.

Display data

with focus on

how data

looks

Readability

Readable by

humans and

machines

Only

Machines

As a conclusion for this part, C# is an

appropriate programming language for

developing proposed tool for this project.

Moreover, XML programming language has

been chosen for creating user friendly graphical

user interface.

5.2 Use Case Diagram

In software engineering, Use Case Diagram

is one of the Unified Modeling Language

(UML) tools that concentrated on the end user

goals rather than developing features. The use

case will present relations between system and

end user or another system [15].

Use case provides a graphical

demonstration for system which is simplified

and can show the details of possibilities. Use

case diagram can present high level view for

system

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In GDC system, the only actor which is

responsible for doing all tasks is network

administrator.

Figure below shows the use case diagram of

GDC system which including eight tasks and

one user in the system. This use case diagram is

presented in this research to help future

researchers.

Figure 20. Use Case Diagram of GDC System.

Use case diagram of GDC system including

8 features that involve Network Administrator:

To enter GDC System,

To enter facility load, IT load and cost of power.

To monitor PUE & DCE

To monitor electricity used per year

To monitor annual power cost and

To monitor annual CO2 footprint.

The first feature, enter GDC system means

enter user and password in order to enter the

system. The second, third and fourth features

are related to data entry to system. The input

data for GDC system is inclusive electricity

usage for IT devices, electricity usage for all

facilities and cost of power used in data center.

Last four steps indicate monitoring of

calculated data such as PUE, total cost and

carbon emission.

Next section provides how the suggested

system features designed in the use case

diagram to be design as Graphical User

Interface (GUI) for future implementation.

5.3 Suggested GUI Design

Basically, the initial design of GUI for GDC

system can be considered to be users friendly

when all the system features had been

organized into four (4) different parts involved

the company logo related to data center and

GDC title, simple buttons which enable

network administrator to calculate cost,

emission and energy, text boxes which allow

network administrator to enter the value of IT

load, facility load and cost per kwh, and last but

not least the PUE result which expected to

contribute to the sustainability of data center.

Figure 21. Initial Design of Graphical User Interface for

GDC.

As demonstrated in figure 21, IT load and

facility load will be shown in a pie chart after

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data entry. Consequently, total cost will be

calculated based on a fixed amount of cost per

kWh and electricity usage. Total carbon

emission and energy usage are measured based

on power consumption thorough a year. The

final part of GUI is related to the PUE which is

illustrated in three sections: very efficient,

efficient, and very inefficient. The result of

PUE indicates how much a data center is green.

6 CONCLUSION

As a summary of this analytical survey,

green data center (GDC) is an important issue

for network administrators and network

managers. Moreover, increasing energy

efficiency, decreasing carbon footprint and

managing costs are significant issues for

monitoring and managing data centers. The

GDC tool proposed in this research to be

simple, user friendly, and efficient in facilitate

8 system features that involve process of to

enter into GDC system, to provide input to

facility load, IT load and cost power, to monitor

PUE, DCE, electricity used per year, annual

power cost and annual CO2 footprint.

ACKNOWLEDGEMENT

The author extends gratitude to any

institution involved for the support in making

the process of converting the final year project

to a research paper a valuable experience to the

author, which integrates the teaching and

learning capabilities into one knowledge

platform.

REFERENCES

[1] ISI Web of Science,

http://thomsonreuters.com/thomson-reuters-web-of-science.

[2] Intel, 2011. “The Efficient Data Center. High Temperature Server Data Center”, pp.33.

[3] U. Mueen, “Energy Efficiency and Low Carbon Enabler Green IT Framework for Data Centers. Renewable and Sustainable Energy Reviews”, 2014.

[4] Bianzino, A. P., 2012. “A Survey of Green Networking Research”, Communication Surveys & Tutorials, IEEE, 14, 20.

[5] Clark, K., 2014. “Cisco LAN Switching. Cisco Press.

[6] R. B. Raffaele Bolla, Franco Davoli, Flavio Cucchietti, 2011. “Energy Efficiency in the Future Internet: A Survey of Existing Approaches and Trends in Energy-Aware Fixed Network Infrastructures”, IEEE Communications Surveys & Tutorials.

[7] T. Hammond, 2013. “Calculate Data Center Server Power Usage”, Computer & Mobile Forensics.

[8] R. H. David Korn, 2012. Computer Power Management for Enterprises [Online], Available at: http://www.terranovum.com/docs/energystar/computer_pwr_mgmt_for_enterprises-practical_guide.pdf [Accessed 17 April 2014]

[9] M. Talebi, 2008. “Computer Power Consumption Benchmarking for Green Computing”, Villanova University.

[10] V. Avelar, 2012. “PUETM: A Comprehensive Examination of the Metric”, The Green Grid, pp.8.

[11] B. Lajervadi, 2014. “An Energy Efficiency Metric for Data Center Assessment”, Oregon State University Energy Efficiency Center, pp.8.

[12] C. Belady, 2008. “Green Grid Data Center Power Efficiency Metrics: PUE and DCIE”, The Green Grid, pp.9.

[13] N. Nrel, 2011. “Best Practices Guide for Energy-Efficient Data Center Design”, Energy Efficiency and Renewable Energy, pp. 28.

[14] Katsirikou, A., 2013. “Qualitative and Quantitative Methods”, Book of Abstracts of the 5th Qualitative and Quantitative International Conference, International Society for the Advancement of Science and Technology.

[15] IEEE-Standard, 2007. “IEEE P2407 Standard for Personalized Health Informatics”, IEEE.

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