MANAGING ENERGY EFFECTIVENESS IN FINNISH DATA

CENTERS

Teemu Muukkonen, Sakari Luukkainen and Antti Yl¨a-J¨a¨aski

Department of Computer Science and Engineering, Faculty of Natural and Information Sciences

Aalto University, School of Science and Technology, Konemiehentie 2, Espoo, Finland

Keywords:

Data center, Energy effectiveness, Interview study.

Abstract:

Energy effectiveness has become a competitive advantage for service providers managing large-scale central-

ized data centers. Technological solutions in this ﬁeld have developed signiﬁcantly in recent years, which

exploitation should be supported by the organizational managament viewpoints. The goal of this study is to

investigate how the companies develop their energy effectiveness and manage the functions connected with it.

Based on multiple company case analysis we identiﬁed nine factors mostly inﬂuencing energy effectiveness.

Derived from these ﬁndings we present ﬁnally a framework for environmental management, which can direct

the organization to improve the energy effectiveness of its data center.

1 INTRODUCTION

The environmental effects of information and com-

munication technology (ICT) have become a topic of

great social signiﬁcance. The electricity consumption

of ICT service infrastructure is increasing and it is

necessary to improve the effectiveness of the energy

usage of ICT devices and infrastructure. Electricity

consumption is a signiﬁcant cost item for the compa-

nies in this ﬁeld and the importance of managing it is

enhanced as a competitive advantage.

End user companies have increasingly started to

outsource their ICT infrastructure to large-scale, cen-

tralized data centers managed by a specialized service

provider. This trend is further enhanced by the prolif-

eration of cloud computing technologies, which en-

able placing applications in the network. Therefore,

in recent years the research into electricity consump-

tion of data centers has become especially active. In

eighteen months, a server consumes electricity worth

its price. This means that electricity costs can account

for even a third of total cost of ownership for a data

center (Belady, 2009; Brill, 2007). During the years

2000-2005, the global electricity consumption of data

centers has grown on the average 17 % per year from

71 TWh to 153 TWh. Their share of total electricity

consumption in the world is 0.8 %. (Koomey, 2008)

The most signiﬁcant Finnish electricity consumer

has traditionally been forest industry. One paper mill

uses 1-2 TWh electricity per year, while the electricity

consumption of all Finnish data centers is ca 1 TWh

per year (M¨aih¨aniemi, 2009). However, the structure

of the industry is changing and ICT services are be-

coming more signiﬁcant branch. Because Finland of-

fers signiﬁcant advantages as a site for data centers

both for domestic and foreign companies, new data

centers are being built. Google, for instance, has just

decided to place its data center in Finland in a closed-

down paper mill. Finland is a favorable site for data

centers because the climate of Finland is cold and the

country has a lot of lakes. In addition, Finland has

a good electricity and communications infrastructure,

skilled ICT labour, no earthquakes or tropical storms

and an internationally competitiveprice level for elec-

tricity.

In addition to technical questions connected with

energy saving it is important to have a wider under-

standing of the organizational viewpoints connected

with their introduction and exploitation. The target of

this research is to investigate how the companies de-

velop their energy effectiveness and manage the func-

tions connected with it. In addition, we present a

framework of environmental management, which can

direct the organization to continuously improve the

energy effectiveness of its data center. We have lim-

ited the research to apply only to data centers, that is

servers, computer network equipment, power supply

and cooling systems.

Muukkonen T., Luukkainen S. and Ylä-Jääski A. (2010).

MANAGING ENERGY EFFECTIVENESS IN FINNISH DATA CENTERS.

In Proceedings of the Multi-Conference on Innovative Developments in ICT, pages 5-12

DOI: 10.5220/0002962200050012

 SciTePress

2 LITERATURE REVIEW

Our literature review consists of two parts. First we

study the literature on environmental management in

general. Then we review the literature on managing

energy effectiveness in data centers.

2.1 Environmental Management

The development and certiﬁcation of environmental

management systems are laborious and time consum-

ing expensive projects. The internal motivational fac-

tors of enterprises are comprised of cost savings, the

effectiveness of resource usage, productivity, the ful-

ﬁllment of environmental regulation, cost reduction,

environmental risk reduction and encouragement to

innovate. The external motivational factors include

an improved public and interest group image, positive

customer feedback, strengthening of market position

and adaptation to legislation. (Rohweder, 2004; Ke-

tola, 2004)

Some research has been made into the success and

proﬁtability of environmental management systems.

One of the the beneﬁts of environmental management

systems is the improvement of effectiveness due to

cost savings. Additionally the operative management

becomes more efﬁcient. These systems reduce envi-

ronmental risks and clarify the handling of disorders.

On the other hand, there are conﬂicting research re-

sults of the effect of systems on image and compet-

itiveness. The effect of the systems on the relations

to the authorities is positive, because the systems in-

crease the knowledge of the regulation. The environ-

ment generally beneﬁts from the systems as the ef-

fectiveness improves. Because the basic principle is

a continuous improvement of environmental matters,

aims can be set as to long-term effects. However,

the environmental management systems do not mo-

tivate companies to innovate to improve products and

services, but emphasize gradual improvement. The

environmental systems are mainly valid in operative

management, but not in a strategic approach. In ad-

dition, their logic is based on manufacturing industry

and doesn’t suit the service business perfectly. (Rin-

nekangas, 2004a; Rohweder, 2004)

In the future the importance of the proactive envi-

ronmental management will increase and the useful-

ness of a separate environmental organization will be-

come questionable (Rinnekangas, 2004b). It seems to

be possible that environmental management will play

a more important role in every manager’s work. It can

be stated on the basis of literature that bringing en-

vironmental matters as part of strategic planning can

yield a competitive advantage as cost savings, better

corporate image, new markets and even as new busi-

ness possibilities.

Energy must be dealt with similarly to other pro-

duction factors from the point of view of the busi-

ness strategy. The energy used by the production pro-

cess of the company can be classiﬁed as a physical

resource. The strategic value of the resource is de-

ﬁned by how much the resource affects the company’s

possibilities, core competence and competitive advan-

tage. (Hitt et al., 2001)

Skilled personnel, equipment, real estate and en-

ergy are the most important production factors of the

ICT companies. Energy-efﬁcient actions are valuable

for data centers valuable and they are difﬁcult to imi-

tate by competitors. If the company is energy efﬁcient

and has access to competitively priced electricity a

permanent competitive advantage is gained. (Barney,

1991)

2.2 Energy Effectiveness in Data

Centers

In this section we provide an overview of energy ef-

fectiveness research in data centers. First we, study

the metrics of data center energy effectiveness. Sec-

ond, we discuss what are major energy inefﬁciency

factors in a data center. Then we analyze the current

and the most common improvements in servers and

data centers.

2.2.1 Energy Efﬁciency Metrics

The most common data center energy efﬁciency met-

ric is the Power Use Effectiveness value (PUE), also

known as Site Infrastructure Effectiveness Factor (SI-

EER). For a data center, PUE is calculated by dividing

the electric power used by the whole data center with

the electric power used by the ICT equipment in the

data center. A PUE value of 2.0 means that site in-

frastructure is using the same amount of electricity as

the computing equipment. The best published PUE

values are about 1.3. The range between 2.0 and 2.5

is considered typical, and rates over 3.0 are consid-

ered poor. A PUE value is comparable between dif-

ferent data centers when it is continuously observed

and presented as an annual mean value or as a graph.

(Szalkus, 2008; Belady et al., 2007; McNevin, 2009)

However, a PUE value does not tell us anything

about the effectiveness of the actual computing inside

a data center. Several metrics, including Data Center

energy Productivity (DCeP), Corporate Average Data

Center Efﬁciency (CADE) and Computing Units per

Second (CUPS) have been suggested but none have

achieved the wide acceptance of the PUE. (McNevin,

2009)

INNOV 2010 - International Multi-Conference on Innovative Developments in ICT

2.2.2 Major Energy Inefﬁciencies in Data

Centers

There are three major inefﬁciencies inside a data cen-

ter. First, heat removal requires additional electric

power. This inefﬁciency has recently become much

worse because serverdevices require more energyand

are packed more densely than ever before. The result-

ing hotspots put the conventional heat removal meth-

ods to their limits. Conventional air cooling meth-

ods can also suffer from multiple inefﬁciencies, as

stated by Robert Tozer. Inefﬁcient use of comput-

ing resources also wastes energy. A server’s energy

consumption remains commonly at 70 % even when

the server is idle. On dedicated physical servers, to-

tal utilization can often be as low as 10 %. Roughly

calculated, this means that a physical server can use

as much as 86 % of the electricity to power idle use.

Third energy inefﬁciency is the losses in electricity

delivery and transformations. While losses in a single

stage are minimal, total losses of consecutivetransfor-

mations can be substantial. (Koomey, 2008; Flucker,

2009; Tozer, 2006)

2.2.3 Energy Efﬁciency Improvements in

Component and System Efﬁciency

In recent years, the competition between processor

manufacturers has changed from frequency-drivento-

wards comparing actual capabilities, even energy ef-

ﬁciency. In the same time, multi-core processors have

become an industry standard. Especially in servers,

this has lead towards more processor cores inside

a computer and thus more concentrated energy use.

This has made heat removal problems both inside a

server and in data centers more crucial. Most recent

processors can reduce energy use by turning off pro-

cessor cores when the processor is idle. (Barroso,

2005; Intel Corporation, 2009).

There have been efﬁciency improvements also in

storage technology both on single-disk and storage

system level. Major technology behind this has been

the transfer form 3.5-inch hard drives to 2.5-inch hard

drives. Next step is said to be the wider use of solid

state drives. This will eliminate mechanical parts

from hard drives and make them even more energy

efﬁcient. On storage systems, also software or algo-

rithm based energy optimization methods have been

suggested. (Sugaya, 2006; Rydning, 2009; Caulﬁeld

et al., 2009; Wang et al., 2008)

AC power sources used in desktop and server

computersoften have poor efﬁciency especially at low

levels of utilization. The 80 Plus certiﬁcation has im-

proved especially desktop computer power sources.

Since the technology used in server power sources is

the same, the same efﬁciency improvements can be

achieved on servers. (Calwell and Mansoor, 2005).

On the server level, the adoption of blade servers

has improved energy efﬁciency. The idea of concen-

trating the power sources has made it possible to make

fewer but better power sources. Current blade servers

have advanced power management features to con-

trol the power used by individual blades and to turn

the power sources of the blade enclosure at on opti-

mum utilization. Blade servers have also indirect efﬁ-

ciency improvements since they reduce the amount of

cabling needed thus enabling better airﬂow inside the

server cabinets. (Leigh et al., 2007)

Operating system level power management is

widely used on desktop systems. Since servers are

supposed to answer queries rapidly almost at any

hour, turning off idle servers is not very common.

However,there has been research on power awareness

in enterprise software and in scientiﬁc computing ap-

plications. (Rajamani and Lefurgy, 2003; Kusic et al.,

2009)

2.2.4 Energy Efﬁciency Improvements:

Virtualization

Server virtualization is a proven way to make a data

center more energy efﬁcient. By placing several op-

erating systems on the same server, virtualization can

cut down the amount of electricity needed to power

idle processors. It is reported that under heavy virtu-

alization, a physical server can have a utilization of

70 percent compared to the worst case utilizations of

dedicated physical servers. Since an idle server has

about 70 percent electricity demand of a fully uti-

lized server, virtualization can cut down electricity

needs signiﬁcantly. (White and Abels, 2004; Crosby

and Brown, 2007; Best Practices Case Studies 2007,

2007; Flucker, 2009)

In addition to energy savings server virtualiza-

tion enables many operative level economical savings

and enables new business opportunities. Compared to

physical servers, virtual servers are more compatible,

portable, manageable, deployable and customizable.

With current virtualization platforms, live migration

and even geographical relocation of virtual servers is

possible. Server virtualization is also an important

enabler of cloud computing platforms. (Crosby and

Brown, 2007; Tsugawa et al., 2006; Boss et al., 2007)

2.2.5 Energy Efﬁciency Improvements in Data

Center Infrastructure

In this section we review some aspects of data cen-

ter infrastructure efﬁciency. Data center infrastruc-

ture efﬁciency is deﬁned by how efﬁciently the infras-

MANAGING ENERGY EFFECTIVENESS IN FINNISH DATA CENTERS

tructure succeeds in provisioning electric power to the

ICT equipment and in removing the heat generated by

the equipment from the data center.

Data center power provisioning is built to achieve

minimum service downtime, not energy efﬁciency.

Eliminating single points of failure in each power dis-

tribution phase is done by heavily exploiting duplica-

tion of components. This leads to inefﬁciencies be-

cause components are not fully utilized. This can be

eliminated by exploiting N+1 mode instead of cur-

rent 2*N model of backup components. There are

also multiple subsequent AC/DC, DC/AC and volt-

age transformations. As a solution, there have been

some suggestions of DC based power provisioning in-

side data centers. While DC power provisioning is an

industry standard in telecommunications, server com-

puters and thus data centers rely on AC power pro-

visioning. By minimizing the transformations, the

power distribution chain can be improved from 77

percent to 90 percent. (Greenberg et al., 2006; Fan

et al., 2007; M¨aih¨aniemi, 2009)

Inclining energy densities and the increased heat

problems inside data centers has naturally resulted in

research about heat removal. Data centers have been

studied by heat cameras or temperature sensors and

the results have been analyzed by means of computa-

tional dynamics. The research has improved the in-

dustry standard of raised ﬂoor air cooling by separat-

ing the hot and cold airﬂows to cold aisles and cold

aisles and by optimizing the perforation in ﬂoor tiles

or enclosing the cabling under the ﬂoor to separate

compartments. The knowledge about dimensioning

the cooling systems is important since the CRACs are

most efﬁcient when fully utilized. By optimizing the

cooling system to enable great energy densities inside

a data center one will reduce ”thermal inertia” and

thus making cooling emergencies more urgent to act

on. (Sharma et al., 2005; Karlsson and Moshfegh,

2005; Rambo and Joshi, 2007; Hamann et al., 2008;

Tozer, 2006)

In cold climates, such as in Finland, free cooling

by outside air, cold water or even the rock beneath

the building can be very efﬁcient. As a further devel-

opment of the idea, heat recycling can be even more

efﬁcient than free cooling. Late 2009 heat recycling

was announced to be utilized in a data center open-

ing in Helsinki, Finland. The extra heat of the data

center is fed to the district heating system of Helsinki.

In addition to this, district cooling system is utilized.

District heating can offer economies of scale to the

cooling. (Greenberg et al., 2006; Pagnamenta, 2010)

3 METHODOLOGY

The research was carried out using the multiple-case

study research methodology. Multiple-case designs

enhance external validity, because methods such as

replication logic and pattern matching can be used to

test the generalization of the results. If similar ﬁnd-

ings are observed in several cases analysed sequen-

tially, a replication has taken place. (Yin, 2003)

Because the research area is new and because it

was difﬁcult to reach a large enough population by a

quantitative questionnaire based method, we decided

to gather the data by interviews. In these interviews

we got widely information of 12 Finnish ICT organi-

zations. In the interviews we investigated those orga-

nization’s attitudes to energy consumption. Key per-

sons responsible for the data centers in various orga-

nizations were interviewed. Most of the interviewees

had much knowledge about data center operations as

a whole. Seven of them worked in a company of-

fering ICT services (we call them hosting companies

or hosting providers), two worked for telecommuni-

cation operators and three in other types of organiza-

tions that were managing the ICT functions internally.

The interviews were carried out as half-structured

interviews, which were built on three interlinked

themes. These themes were environmental and busi-

ness management as well as technology aspects. A

typical interview lasted about one hour.

The validity of the patterns that had been found

was ensured by the pattern matching. Furthermore,

the usage of multiple sources of evidence, or trian-

gulation is hi-lighted (Yin, 2003). That is why the

framework and related dimensions were integrated

from a multiple data sources (literature, interviews,

articles, annual reports and press releases). The limi-

tation of the study only to Finland restricted the num-

ber of the available cases. The generalizability of the

research ﬁndings is thus restricted to Finnish context

and only to the hosting providers. However, there is

still the possibility in further studies to test the results

derived from these cases in other geographical areas

and company segments.

4 RESULTS

We listened the recordings of the interviews and rec-

ognized the following themes and frequencies in the

whole sample. The themes were brought up by the

interviewees or inherent in multiple answers to our

questions. We show here the themes that were present

in at least half of the cases or at least in ﬁve of the

seven hosting companies. Frequencies of the themes

INNOV 2010 - International Multi-Conference on Innovative Developments in ICT

in interviews are presented in Table 1.

Table 1: Frequencies of the themes in interviews.

Theme Total Hosting

Virtualization 9 6

Buildings 8 4

Electricity Costs 8 6

Availability 7 4

Heat recycling 7 5

Billing the electricity 7 6

Airﬂows 6 5

Centralization 6 5

Life Cycle 5 5

4.1 Virtualization

Virtualization was mentioned in almost all of the in-

terviews. The most signiﬁcant beneﬁt of virtualiza-

tion was the improved utilization of servers, storage

system and network equipment. This means savings

in costs and electricity.

4.2 Buildings

Most data centers had been built in the 1980’s or

1990’s. While building them, there were no pro-

jections to account for the heat densities or power

requirements of recent blade servers. Adding more

CRACs or electricity inputs is impossible or very ex-

pensive because of the structures of the building. This

theme was relevant in all the interviews, regardless of

the organization type.

The following themes were present distinctively at

the sample of hosting companies.

4.3 Electricity Costs

Electricity costs are signiﬁcant part of service deliv-

ery. Since this is now known throughout the indus-

try the electricity costs are also minimized by at least

some of the companies. When these companies trans-

fers the electricity savings to their prices the effective

market system will force the others to optimize their

electricity use.

4.4 Availability

Availability is important for hosting business. Cus-

tomers trust their data and applications in the hand

of the hosting companies. That is why the hosting

providers use duplicated equipment to eliminate sin-

gle points of failure from their systems which in turn

leads to declining energy efﬁciency.

4.5 Heat Recycling

Almost all of the interviewed organizations have in-

vestigated the possibility of heat recycling. The prob-

lem there was that the energy providers or facility

companies are only interested in investing in the heat

recycling of major data centers. Some interviewees

mentioned having heard about the concept of feeding

the exhaust heat to the district heating system and uti-

lizing district cooling to cool down the data center.

4.6 Billing the Electricity

At the time of the interview three of the seven host-

ing providers were appraising the electricity costs to a

single provided service and three organizations were

investigating a similar arrangement. Many intervie-

wees thought that making the energy cost visible in

customer or internal billing would guide both exter-

nal and internal customers to demand more energy

efﬁcient solutions.

4.7 Airﬂows

Five of the seven hosting providers told that they

have had airﬂow problems inside their data centers.

Main solution to the problems had been separating

the hot and the cold airﬂows more efﬁciently either

by hot and cold isle method or by blocking the air-

ﬂow through an empty or partly ﬁlled rack cabinet.

Distributing the most heat intensive devices evenly

around the data center was mentioned as a working

solution.

4.8 Centralization

Five out of seven interviewees representing hosting

providers introduced the theme about the efﬁciency

of centralized service production. By consolidat-

ing service production to the data centers of host-

ing providers even small businesses could exploit the

economies of scale. Efﬁciency results from follow-

ing two things. First, the hosting providers are able to

organize the energy issues of servers better than small

businesses. Second, by consolidating the services, the

equipment will run at a higher utilization rate.

4.9 Life Cycle

Server computers, storage equipment and networking

equipment have a life cycle of three to ﬁve years. The

whole data center lifecycle varies from ﬁve to twenty

years. Hosting providers have knowledge about ICT

MANAGING ENERGY EFFECTIVENESS IN FINNISH DATA CENTERS

energy issues, but this knowledge can be fully ex-

ploited only in new data center projects. The exist-

ing data centers are not utilizing all of the current best

practices.

5 CONCLUSIONS

Themes presented above were all very common

amongst the interviewees and their organizations.

Most of the themes can be categorized as incentives

or inhibitors for ICT energy efﬁciency. To success-

fully improve ICT energy efﬁciency an organization

has to remove inhibitors and strengthen the incen-

tives. Based on the interviews, an organization’s abil-

ity to act on inhibitors and incentives is greatly af-

fected by the life cycle of the system which carries an

inhibitor or an incentive. By analyzing the incentives

and inhibitors and by ﬁnding the inhibitors that can be

rapidly removedthe organizations could improve ICT

energy efﬁciency more rapidly.

We suggest the following framework to improve

the organizations’ abilities in analyzing various incen-

tives or inhibitors of energy efﬁciency improvements

inside the data centers. The framework is presented in

the form of a four ﬁeld matrix, as represented in Fig-

ure 1. The vertical axis separates the incentives or in-

hibitors based on their life cycle, short being less than

three years and long being over three years. The hor-

izontal axis separates the incentives from inhibitors.

The quadrant tells the user of the tool what to do

about the incentive or inhibitor, whether to eliminate

the inhibitor immediately, eliminate the inhibitor dur-

ing renovations, periodically or continuously assess

the incentive an its impact on ICT energy efﬁciency.

Long

Short

Inhibitor Incentive

Fix during

renovation

Fix immediately

Continuous

assessment

Periodical

assessment

LIFE CYCLE

Figure 1: The framework used in reason analysis.

In Figure 2 we represent the relevant themes from

the interviews using the matrix introduced above. A

Long

Short

Inhibitor Incentive

LIFE CYCLE

Centralization

Buildings

Airflows

Availability

Billing the

electricity

Virtualization

Electricity costs

Heat recycling

Figure 2: Themes represented by our framework.

fast way to improve energy efﬁciency in different or-

ganizations is to present the energy issues as cost to

the ICT management or the customers. Availability

can be rethought to be provided more energy efﬁ-

ciently or not to be implemented in systems not really

needing high availability infrastructure. Also, opti-

mizing the airﬂow in the current data center can result

in remarkable efﬁciency improvements very rapidly.

Airﬂow planning is also an important part in building

new data centers or renovating the old ones. Problems

in facility infrastructure can only be attended during

renovations or relocations.

Cost pressure caused by the industry competi-

tion is a relevant incentive driving energy efﬁciency

amongst the hosting providers. Centralization or

consolidation is a theme emphasized by the hosting

providers but there is no empirical evidence support-

ing this result. Wide adaption of server virtualization

is an important energy efﬁciency driver for all ICT

activities in both short and long lifecycle.

6 FUTURE RESEARCH

Based on our research we suggest the following re-

search areas. The presented framework is based

on twelve interviews in one geographical area and

mainly inside one industry. Generalizability of the

framework requires more empirical evidence.

A thorough, holistic and comparative study about

the energy efﬁciency differences in centralized and

distributed service production would help in conﬁrm-

ing the hypothesis of centralization’s positive effect

on ICT energy efﬁciency stated by many intervie-

wees. Data center energy efﬁciency metrics should

also be continuously investigated, especially the ones

concentrating on efﬁciency of the computing.

INNOV 2010 - International Multi-Conference on Innovative Developments in ICT

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