Cloud Computing: Grey or Green?

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Brassersplein 2 2612 CT Delft Postbus 5050 NL-2600 GB Delft www.tno.nl T +31 88 866 70 00 F +31 88 866 70 57 [email protected] TNO report 35649

Cloud Computing:

Grey or Green

?

On the energy-efficiency and sustainability of

Infrastructure-as-a-Service

FINAL VERSION

Date 23 March 2012

Original Author(s) Mark Bastiaans, Bram Spitzer, Daniël Worm, Freek Bomhof English Translation Commissioned by SURF

Review Pieter Meulenhoff Number of pages 33

Number of appendices:

2

Client NL Agency [AgentschapNL]

Steering group Frank Hartkamp (NL Agency), Dirk Harryvan (MAN Systems), Gerard van Westrienen (SURF), Jan-Willem Tellegen (Green IT Consortium Amsterdam), Paul Dekkers (SURF)

Project name Green Clouds Project number 055.01464

This publication is subject to Creative Commons licence “Attribution – Non-commercial – No Derivative Works” (CC BY-NC-ND 3.0).

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Management Summary

Cloud Computing: Grey or Green?

On the energy-efficiency and sustainability of Infrastructure-as-a-Service

Organisations that wish to reduce their energy consumption find themselves faced by a number of choices. One of these choices is to reduce the amount of energy consumed by their ICT. This choice brings further options, the one beingto address the consumption workstations by means of active energy management, the other to address the consumption of the servers. “Cloud computing” is receiving increasing attention in connection to the consumption of servers: it can help reduce costs. It is often believed that cloud computing is automatically energy-efficient. This is not necessarily so; in fact, cloud solutions can vary considerably in this respect.

Cloud computing is defined as “on-demand, dynamic access to a collection of ICT resources (such as networks, storage, processing, applications, and services) over a network”. This involves more than merely using service such as webmail or web-based documents. Organisations often choose cloud solutions due to the cost advantages: capacity that is only needed temporarily is only utilised (and paid for) when it is really necessary.

This study focuses on “Infrastructure-as-a-Service” clouds – i.e. clouds in which storage and processing capacity is made available as a service – with the main focus on the question “When is a cloud green?”. “Green” in this context is defined primarily in terms of energy consumption, but the associated CO2 emissions are also considered, i.e. the sustainability of the process of generating the consumed energy.

The energy consumption of a cloud depends mainly on the efficiency: is all ICT equipment fully utilised? An unused server could be turned off or phased out. Cloud computing offers the possibility of utilising dynamic ICT resources, i.e. it enables turning resources on and off as and when necessary. It also enables optimally utilizing the ICT resources that are available. Often the use of cloud computing alone implies improved efficiency. The effectiveness of the energy consumed – effectiveness being the proportion of the energy is used for ICT and how much is needed for cooling systems and other support equipment - is also relevant. Another factor that needs to be taken into account concerns the emissions resulting from the energy consumption.

Specifically for cloud computing, location also plays a role. A cloud is characterized by storage and processing take place at a certain distance from the end-user. Therefore, The energy that networks consume in order to transport the data must also be taken into account. Cloud computing also enables that storage and processing takes place at a location where energy – i.e. locally generated energy – is cheapest (including the transport costs) and greenest.

An organisation that intends to make use of “green clouds” will likely assess cloud providers by means of frameworks such as the CO2 Performance Ladder. For cloud providers, some of the main considerations for providing “green clouds” will be promoting efficient use and implementing effective capacity management. For cloud

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customers, energy efficiency, energy effectiveness, and emissions by the services utilised should be considered in internal (TCO) calculations.

A summary of the most important features: A cloud provider is greener if:

• The servers are fully utilised: the number of servers that are switched on but are not doing any useful work has been minimised (efficiency); techniques that can be used to this purpose are e.g. virtualisation, scheduling and provisioning and energy-efficient hardware;

• The energy that the data centre consumes is mainly consumed by the servers; in reverse: only a minimum of energy is necessary for cooling, lighting, and other systems (effectiveness); frameworks and metrics that can be used to measure effectiveness include frameworks such as OpenDCME, BREEAM, LEED and metrics such as Green Grid;

• The energy consumed leads to the minimum possible emissions; in other words, it has been generated sustainably;

• The data centre is not too far away from the users so that transporting the data consumes less energy;

• The energy is generated at a location close to the data centre so as to minimise transport losses.

Cloud service customers should take the following into account:

• Provider assessment by means of a framework such as the CO2 Performance

Ladder;

• Inclusion of energy efficiency (or another sustainability metric) in their own management systems and management reports;

• Allow for the energy efficiency of ICT use in the internal pricing for services; • Encourage efficient use, e.g. by encouraging that computationally intensive but

non-interactive tasks (that cause little network traffic) are processed within the cloud.

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Summary

Cloud computing is on demand, dynamic access to a collection of ICT resources (such as networks, storage, processing, applications, and services) over a network. This study assumes “Infrastructure-as-a-Service” clouds: storage and processing capacity is made available as a service, either as a public cloud (at one or more central locations for various customers), as a private cloud (the customer creates its own cloud for its own end-users), or as a federated cloud (different customers share their cloud facilities with one another, consequently also acting as providers for one another). A federated cloud that is used within a closed group – for example only by participants from a single sector – is sometimes called a “community cloud”. Cloud computing offers advantages: it can be both cost efficient and energy-efficient compared to ICT that is managed in the traditional way by individual organisations. This report concerns the question “When is a cloud green?” In this study, we look at “green” primarily in terms of energy consumption, but the related CO2 emissions are also considered: how sustainable was the process of generating

the energy consumed?

The energy consumption of a cloud depends mainly on the efficiency: are the ICT resources all actually utilised to the full? A server that is not actually used can perhaps better be turned off or phased out. Cloud computing offers the possibility of utilising dynamic ICT resources – in other words turning them on and off as and when necessary – and also of making optimum use of the ICT resources that are available. The use of cloud computing already often means improved efficiency. The effectiveness of the energy consumed is also relevant: what proportion of the energy is used for ICT and how much is needed for cooling systems and other support equipment? Another factor that needs to be taken into account concerns the emissions resulting from the energy consumption.

Specifically in the case of cloud computing, the location also plays a role. It is characteristic of a cloud that storage and processing take place at a certain distance from the end-user. The energy that networks consume in order to transport the data must therefore be taken into account as well. Cloud computing also makes it possible for storage and processing to take place at a location where energy – i.e. locally generated energy – is cheapest (including the transport costs) and greenest. An organisation that intends to make use of “green clouds” will assess cloud providers by means of frameworks such as the CO2 Performance Ladder. For cloud

providers, some of the main considerations for providing “green clouds” will be promoting efficient use and implementing effective capacity management. For cloud customers, energy efficiency, energy effectiveness, and emissions by the services utilised can be allowed for in internal (TCO) calculations.

The ICT architect working for a cloud provider that wishes to set up a “green cloud” will need to take a number of matters into consideration. These include maximising utilisation through virtualisation, efficient scheduling and provisioning methods, selection of the location (for example a location close to the end-user or close to the power station), use of energy-efficient ICT and related resources, use of sustainable energy, and sustainably constructed data centres.

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1 Introduction

1.1 Background: the rise of cloud computing, green ICT

The topic of cloud computing is receiving increasing attention in the world of ICT. Compared to traditional ICT, it is seen as a means of dealing more efficiently and effectively with the available sources such as hardware and energy. A Forrester report refers to cloud computing as an aid to speeding up “green ICT” and mentions the aspects of energy efficiency and resource efficiency.1

In the Netherlands, NL Agency [Agentschap NL] and SURF are collaborating with a number of parties – with efficiency and effectiveness in mind – to determine how to set up a “community cloud” for certain target groups, for example the higher education and research sector. Under the designation “green ICT” a lot of work has also been done nationally and internationally to improve the energy efficiency of individual data centres in particular. This has resulted in indicators, measures of performance, technology, best practices, and practical guidelines. NL Agency has requested TNO to survey the current relationship between “cloud” and “green” and to draw up a report that can assist in deciding on and constructing a “green cloud”. 1.2 The problem to be considered: green, but when and how?

NL Agency works to encourage the various sectors of the Dutch economy, including the ICT sector, to be energy-efficient. This has resulted in a number of Long-term Agreements (in Dutch “MJAs”) with various sectors. The advent of cloud computing has led to NL Agency wishing to determine how this type of ICT service delivery can be made as energy-efficient as possible.

This report attempts to answer the following questions: 1. When is a cloud solution “green”?

a. What is a “green” cloud?

b. What factors are important in attempting to achieve “greenness”? 2. How can a cloud be made green?

a. What changes are necessary within organisations for there to be a green cloud?

b. What service models and business models contribute to a green cloud?

c. How can the design and practical implementation of ICT be made green?

Finally, the report considers what concrete steps can make a cloud greener, in other words how a green cloud can actually be created.

1.3 Scope: IaaS clouds; environmental effect of energy consumption, CO2

This report deals specifically with Infrastructure-as-a-Service clouds (IaaS); when used in this report, the term “cloud” refers to such clouds. The report does take

1_{Cloud Computing Helps Accelerate Green ICT}

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account, however, of both infrastructure and application aspects: an IaaS service is often a service that is not purchased by end-users but by an IT organisation. That organisation will construct applications and services for end-users based on an IaaS service and those applications and services are often a decisive factor in using the IaaS cloud.

This report takes energy consumption and therefore also CO2 emissions (as CO2

equivalents) as the measure of environmental impact (“greenness”). The report does not attach any value judgment to the environmental effects of CO2 emissions.2

In addition to the environmental impact of CO2 emissions, there are other

environmental effects that can play a significant role. One example involves the way extracting and processing many of the rare earth metals used in electronic equipment has a toxic impact on the environment. Large areas are also often affected by extraction. Some energy generation produces radioactive waste. This report does not deal with these environmental effects but that does not mean that they are unimportant.

2_{Indirectly, a consequence is associated with the emission of greenhouse gases: it is linked to a}

weighting (IPPC 2007 100a). That weighting means that each greenhouse gas is assigned a value with respect to CO2. N2O, for example, has a value of 298 kg CO2-eq/kg.

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2 When is a cloud “green”?

This section of the report deals with the question “When is a cloud green?” That question can be broken down into the following components:

a. What is a “green” cloud? A definition is provided.

b. What factors are important in determining “greenness”? An indication will be given of how each factor can be expressed.

2.1 What is a “green” cloud?

In order to define a “green cloud”, we need to consider the terms “green” and “cloud”.

2.1.1 Cloud: dynamic ICT, on demand, payment according to usage

The most frequently quoted definition of “cloud” is that by the United States National Institute of Standards & Technology (NIST).3

“A model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.”

That definition can be summarised as “on demand, dynamic access to a collection of ICT resources (such as networks, storage, processing, applications, and services) over a network”. This report will deal with one specific services model, namely “Infrastructure-as-a-Service” (IaaS), i.e. the provision as a service of the basis for every ICT service: storage and processing.

As an analogy to cloud computing, we can take the availability of a taxi pool. Customers can temporarily hire the taxis and on demand: one pays only for using the taxi; management and maintenance are dealt with by the taxi company. This is different to in-house ICT, which can be compared to a company owning its own fleet of cars. The taxi analogy is used in this report to illustrate a number of aspects of green clouds.

In the case of a cloud, there are two types of stakeholders: providers and customers. The provider supplies the cloud service (storage or processing capacity) while the customer purchases it. An organisation within a cloud chain can in fact act as both provider and customer. Unlike with in-house ICT, the bandwidth and quality of the network connection between the provider and the customer is essential because the cloud provider may be located a great distance away from its customers geographically.

Not only does the geographical distance between supply and demand require even greater attention to the interconnecting network than in in-house IT scenarios, it

3_{NIST definition of cloud computing:}

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often also raises organisational and legal issues. Those issues will not be dealt with in the present report because they are separate to the specific problem to be considered.

2.1.2 Green: minimising the carbon footprint per business unit

In an IaaS cloud, the physical location, ownership, and management of the ICT resources of storage and processing have shifted towards the provider. This means that the provider can not only pool ICT resources so as to utilise them more effectively and efficiently; increased scale also means that it can deal more effectively with suppliers. This means not only that fewer ICT resources will be needed in order to meet the total combined demand by customers; the total amount of energy consumed in order to operate those resources will also be lower because the customers themselves will need to keep less (over)capacity operational (or indeed none at all).

In this report, “green” is taken to mean minimising the carbon footprint per business unit. To continue the taxi analogy: “green” means minimising the quantity of CO2 released due to use (combustion of

fuel) and the CO2 involved in manufacturing and

scrapping the taxi, calculated per passenger. The use component of the carbon footprint depends on the energy consumption of the taxis in the pool when

they are on the road, while the

manufacturing/scrapping component depends on the consumption of materials when the taxis were manufactured.

In the case of ICT, these terms can be defined as follows: Carbon footprint: the carbon dioxide impact during:

• the use phase. This comprises the emissions due to the energy

consumption relating to the use of ICT resources. This component is variable depending on the use made of the equipment concerned. • the manufacturing and scrapping phases. This involves the resources

themselves and therefore such things as the consumption of materials (embedded carbon) and energy consumption involved in manufacturing and scrapping the resources. This component is not variable and can only be influenced when purchasing equipment.

2.2 What factors are important in attempting to achieve “greenness”? For ICT in general, three factors are relevant in attempting to achieve greenness in the use phase, i.e. minimising the carbon footprint:

• the efficiency and effectiveness of the energy consumption; and

• the greenness factor, which is dependent on the emissions due to energy consumption.

This report assumes that these three factors are far less significant during the manufacturing and scrapping phases than in the use phase. Section 2.2.1 explains why that is the case.

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There are a number of aspects that need to be taken into account in calculating these factors specifically for cloud computing. The factors themselves and the cloud-specific aspects will be explained below. Annex A explains how the various different factors can be combined into a single “greenness figure”.

2.2.1 Efficiency and effectiveness: minimising energy consumption

As we have already seen, the carbon footprint – and therefore the greenness – can be divided up into a use component and a manufacturing/scrapping component. The ratio between these two components is extremely important. An EU report notes that in the case of office computers the ratio between the carbon footprint in the use phase and during manufacturing/scrapping (given a five-year write-off period) is approximately 66 : 33.4 Estimates for servers – which are switched on longer than office computers and more fully utilised – suggest a ratio of 90 : 10.5 The above estimates indicate that the greatest benefit can be achieved by minimising energy consumption per business unit. In the case of the taxi, the energy consumption involved in conveying a single passenger must be minimised. This can be achieved by utilising energy as usefully as possible, i.e. as regards both the efficiency and effectiveness of the energy consumption. In taxi terms, these two concepts can be explained as follows:

Efficiency: the level of utilisation of the taxi pool, i.e. the ratio between:

• How many people are conveyed by the taxis; and • How many people fit in the whole pool.

In practice, a taxi company that owns the taxis in the pool will attempt to convey as many people as possible. This will optimise the utilisation per taxi and also the size of the pool. Effectiveness: the relationship between:

• The energy consumption of the taxi pool, i.e. the energy consumed in order to convey passengers; and • The total amount of energy needed to convey

passengers, i.e. including the energy needed for such things as garaging and servicing the taxis.

In actual practice, a taxi company will purchase economical taxis that do not require much servicing, and will deploy a mix of larger (i.e. more effective) and smaller taxis. This means that not only the amount of energy consumed for servicing will be reduced but also the quantity of embedded carbon in the necessary garage facilities.

4_{European Commission DG TREN Preparatory studies for Eco-design Requirements of EUPs}

Lot 3: Personal Computers (desktops and laptops) and Computer Monitors Final Report (Task 1-8)

5_{Fact File: Carbon Reduction Measures - GLA}

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For ICT in general, these two factors can be defined as follows:

• Effectiveness: The ratio between ICT service-related energy

consumption and other energy consumption, where:

o ICT service-related energy is actually consumed for storing and processing information (servers, storage, and internal network connections); and

o Other energy consumption for everything else (for example management, accommodation, cooling, external network connections, energy transport costs).

• Efficiency: the utilisation of ICT-related resources, i.e. the extent to which the ICT resources are actually utilised.

2.2.1.1 Metrics: Compute Efficiency and Power Usage Effectiveness

Work has been going on in the world of green ICT for some years now to create metrics for efficiency (Compute Efficiency; cE) and effectiveness (Power Usage

Effectiveness; PUE). Figure 1 shows the relationship between the various different

types of energy consumption associated with ICT resources and frequently used metrics for the effectiveness and efficiency of ICT. These metrics are described in Annex A.

Other energy consumption (accommodation, cooling,

management,...) ICT service energy consumption (clients,

servers)

Utilisation of ICT service energy consumption

PUE(x)

Energy Consumption

ScE, DCcE

Figure 1 - Energy consumption by a party within the chain

Efficiency and effectiveness can not be viewed separately. A provider can “greenwash” a data centre by making it more effective overall by installing effective resources, but if those resources are not fully utilised, the energy consumption per business unit may in fact be increased.

2.2.2 Greenness factor: emissions from energy consumption; embedded carbon

Minimising energy consumption does not automatically result in a greener cloud. For the cloud to be genuinely green, efficiency and effectiveness must be combined with the following factors:

• Emissions from energy consumption, i.e. the “greenness” of use; and • Embedded carbon, i.e. the “greenness” of manufacturing and scrapping. These two factors will be explained below. As already mentioned, embedded carbon is less important than emissions.

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2.2.2.1 Emissions from energy consumption: CO2 emissions per kWh

Energy consumption can be reduced by means of effectiveness and efficiency. Greenness, however, involves more than those two criteria: the emissions from the type of energy consumed are also relevant. Here too, this factor can not be viewed separately if we wish to prevent “greenwashing”: an efficient and effective provider that utilises grey electricity may be less green than a provider that is less efficient and effective but that uses green electricity.

To continue the taxi analogy:

Emissions: the carbon dioxide released during the

combustion of fuel (for example diesel, petrol, electricity) that the taxi utilises.

In practice, a green taxi is only genuinely green if it causes the minimum possible emissions. The CO2 emission level per kWh

has been calculated for various different fuels and methods of generating energy, ranging from petrol to gas and from coal to wind.

2.2.2.2 Embedded carbon: use of energy and materials; emissions during scrapping

When calculating the embedded carbon in ICT resources, account is taken of their manufacture and scrapping. In the case of manufacture, it is relevant which materials are used. Different materials involve different extraction and processing methods, meaning that the energy required to manufacture a given product will differ. In the case of the manufacturing of a product, all the CO2 emissions are

taken into account, from extraction of the raw material to the actual product.

The materials used are also important where scrapping ICT equipment is concerned. Some materials – in particular metals in their pure form – can be recycled effectively, thus reducing CO2, because no new raw materials need to be

extracted. Plastics, however, are frequently incinerated; this causes the emission of CO2 (in addition to generating a small quantity of energy). Table 1 gives an

indication of the embedded carbon in client hardware (desktop PCs, laptops). Table 1 - Embedded carbon in client hardware electronics. Based on IPCC 2007 GWP 100a V1.02, data from > 2005 (source: TNO)

Appliance Embedded kg CO2)

Desktop PC (without peripherals) 271

Laptop 610

CRT monitor 253

LCD monitor 6392

Keyboard 26

Mouse 5

2.2.2.3 Metrics: emission factor for energy

The emission level per kWh is known for numerous different types and mixes of energy (for energy from mixed sources, for example both coal and water power). It is therefore possible to determine an emission factor for the type of energy used that complements the efficiency and effectiveness and metrics. Annex A explains

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how these emissions can be taken into account when attempting to achieve greenness.

2.2.3 Cloud-specific: network between provider and customer is “other consumption”; allow for cost of transporting energy

Providers and customers within a cloud chain are connected by a network (Figure 2). Network connections consume energy. Estimates in an IEEE report state that as storage and processing shift entirely into the cloud, the proportion of energy utilised for transport will be 10% (private cloud) to 25% (public cloud) of the total.6 However, the efficiency and effectiveness of a cloud can save so much energy that it may be worthwhile incurring these “extra” energy costs; after all, they can be amply compensated for.

ScE, DCcE

Other energy consumption (accommodation, cooling,

management,...) ICT service energy

consumption

... ...

Network PUE(x)

Chain Energy Consumption

Figure 2 – Energy consumption by a chain

Total energy consumption must consequently be viewed as a problem for the chain as a whole, in which the energy consumption of the network is also being minimised. Given that the network between provider and customer is an essential component of a cloud chain but not a primary service (in the case of IaaS the primary services are storage and processing), the energy consumption of the network connecting provider and customer must be categorised as part of other energy consumption.

Transporting information via a copper or optical fibre network and transporting electricity via high/medium/low-tension cables both consume energy. In the United Kingdom, for example, transmitting electricity “costs” 2% in transmission losses.7 A cloud provides the option of consolidating storage and processing, both in house and externally. It may perhaps be better to relocate storage and processing to where energy is cheapest or cleanest rather than bringing cheap or clean energy to the location. This literally means bringing energy to the provider/customer or vice versa. The cost of transporting energy therefore needs to be taken into account when determining energy consumption.

6_{Green Cloud Computing: Balancing Energy in Processing, Storage, and Transport}

Jayant Baliga, Robert W. A. Ayre, Kerry Hinton, Rodney S. Tucker (IEEE Fellow) http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05559320

7_{Investigation Into Transmission Losses on UK Electricity Transmission System – June 2008}

http://www.nationalgrid.com/NR/rdonlyres/4D65944B-DE42-4FF4-88DF-BC6A81EFA09B/26920/ElectricityTransmissionLossesReport1.pdf

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3 How can a cloud be made green?

This section of the report deals with how a cloud can be made green. That question can be broken down into the following components:

a. What changes are necessary within organisations for a green cloud? In general, this section will deal with greenness within organisations; cloud-specific aspects will not be considered.

b. What service models and business models contribute to a green cloud? Here, consideration will be given to the use and service delivery

aspects of green clouds.

c. How can the design and practical implementation of ICT be made green? Here, consideration will be given to the ICT infrastructure

elements under clouds.

A summary of criteria and measures can be found in Annex B.

3.1 What changes are necessary within organisations for a green cloud? We will deal below with organisational aspects associated with ICT-related greenness within an organisation.

Greenness criteria and measures are:

Who? Criterion Measure(s) Factor

Customer Ensure green policy; from strategy to ICT architecture to procurement

Assess organisations with the aid of the CO2 Performance

Ladder or similar framework(s); choose which. - Provider, customer Make greenness transparent Implement a greenness performance management system for internal and external use.

-

3.1.1 Ensure green policy; from strategy to ICT architecture to procurement

Currently, most organisations are driven by effectiveness and efficiency. In order to be truly green, specific targets are necessary regarding emissions (for example a reduction in tons of CO2).

Organisations will include these criteria as a CSR target in their strategy. However strategy alone is not enough. Most operational processes will focus on achieving the targets as efficiently and effectively as possible from a financial point of view. Here, however, emissions are often ignored and “green” is interpreted as “as cheaply as possible” (i.e. efficient and effective energy consumption). Certain organisations (including manufacturers with a particular production capacity and energy suppliers with a certain generating capacity) are tied to the purchasing of emission rights and it is standard practice to simply “buy off” those rights. Research has shown that the costs for this will be passed on to the organisation’s customers without the intended greenness effect being achieved.8 Efforts to achieve

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greenness will therefore need to be at the level of the individual process, beginning with the ICT architecture process.

The ICT architecture process converts the organisation’s strategy into ICT strategy and design (and vice versa) and consequently plays a key role in minimising the carbon footprint of ICT. By implementing measures in the area of consolidation and standardisation (including application rationalisation, service provision, virtualisation) at service and infrastructure level, ICT resources are made more uniform and can be pooled, and cloud principles can be applied. Those principles alone can already make it possible to achieve greater effectiveness, improved efficiency, and/or lower emissions. A number of these measures are described in the following sections of this report. Other operational processes will need to support these measures.

One operational process that will need to provide this support is the ICT procurement process. In order to incorporate greenness here, emissions would need to be an important factor in the procurement process. The CO2 Performance

Ladder (originally developed by ProRail) is a way of encouraging CO2-aware action

on the part of companies tendering for contracts, both in their own operations and when implementing projects. This involves, in particular, energy-saving measures, the efficient use of materials, and the use of sustainable energy.9 The ladder (Table 2) can be viewed as a maturity model for green-aware organisations; it indicates various maturity levels for various different aspects.

Table 2 - The CO2 Performance Ladder (skao.nl)

Level Description

5 The company has a CO2 emissions inventory of its most important suppliers. The company can demonstrate that the

objectives for levels 3 and 4 have been attained. The company is publicly committed to a government or NGO CO2 reduction

programme, and is able to demonstrate that it is making a relevant contribution to an innovative CO2 reduction project.

4 The company has identified its chain emissions in outline terms, and chain analyses have been carried out for two relevant chains. The company has quantitative objectives for its chain emissions. The company is in dialogue with relevant parties (government bodies and social organisations) and can demonstrate its role as the instigator of sector and chain initiatives in the field of CO2 reductions.

3 The company has an official CO2 emissions inventory that has been drawn up in accordance with the ISO (GHG) standard,

and which has been verified by an independent organisation. The company has quantitative objectives for its own (scope 1 and 2) CO2 emissions. It communicates – internally and externally – in relation to its CO2 footprint on a structural basis and

actively participates in at least one sector and chain-based CO2 reduction initiative.

2 The company has quantified its energy flows and formulated a qualitative objective for saving energy and using renewable energy. Internally, the company communicates its energy policy on a structural basis and takes a passive role in at least one sector and chain-based CO2 reduction initiative.

1 The company has identified its energy flows in qualitative terms and has a list of potential options for saving energy and using renewable energy. Internally, the company communicates its policy in relation to energy-saving and renewable energy on an ad hoc basis and is aware of sector and chain-based CO2 reduction initiatives.

James J. Murphy and John K. Stranlund - University of Massachusetts Amherst - Department of Resource Economics - Working Paper No. 2004-5

9_{The CO}

2 Performance Ladder:

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3.1.2 Make greenness transparent

Besides greenness needing to be incorporated into the way an organisation works, it will also need to be measured and reported at all levels of the organisation. Performance management – i.e. measuring whether processes operate as they are intended to operate – covering effectiveness, efficiency, and emissions will need to be available at all levels of the organisation, ranging from real-time ICT monitoring tools to management dashboards. This transparency applies not only internally – for managers and employees – but also externally: reporting on greenness will not only need to benefit the external fulfilment of an organisation’s CSR targets but also the actual impact of these on the organisation prior to “greening”.

One example of an organisation that is attempting to make greenness transparent throughout the organisation is Google.10 Another example is the above already mentioned GreenQloud, who indicate the level of greenness of their provisioned cloud services in understandable terms such as the number of barrels of oil used or the number of miles driven by a car. Various metrics will need to be utilised at different levels of the organisation; PUE says little in the language of company “targets”, but the carbon footprint per user, citizen, student, or transaction does. In order to apply this metric, the detailed metrics described in the previous section can be utilised at lower levels.

3.2 What service models and business models contribute to a green cloud? We will deal below with supply and demand measures to make a cloud greener. What is relevant here is the interplay between customers for IaaS services and those – within ICT organisations, often the service manager – who provide them. Greenness criteria and measures are:

Provider Make efficiency and effectiveness the basis for ICT architecture.

• Promote efficient use: non-interactive services; spot instances. • Consolidate ICT resources and implement capacity management. Efficiency, effectiveness

Customer Make it attractive for the (internal) end-customer to purchase green services.

Include greenness in (internal) pricing (TCO) so as to guide demand towards greenness.

-

3.2.1 Make efficiency and effectiveness the basis for ICT architecture

Research by the IEEE5 has shown that – besides the fact that energy consumption by networks within the cloud chain can increase to some 25% of total consumption – the network is most heavily loaded – and therefore most utilised – when use is

10_{Google Green}

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made of interactive services. Energy consumption will be greatest in the case of intensive interactive use of virtual machines and hard disk space over the network, for example when a remote desktop or thin-client environments are provided; consumption will be lower with less interactive use, for example large-scale computing jobs which – once started – require little interaction. It is therefore important for the service manager to optimise this kind of use, for example by locating interactive cloud services closer to home (thus requiring a shorter connection) or not in an IaaS cloud at all.

Secondly, efficient use of the cloud can be promoted by means of pricing. Measures that have already been taken in order to set up a cloud – including consolidation of ICT resources and capacity management (by type and number of resources) – often mean greater effectiveness but not greater efficiency. In order to increase efficiency – i.e. to maximise utilisation of a cloud – it is important to run as much storage and processing as possible (virtual machines and “storage buckets”) in the cloud at any moment of the day (“load balancing”). The service manager can influence behaviour on the part of end-users of an IaaS cloud, for example the time when they make use of the cloud. Amazon – the biggest IaaS provider – offers “spot instances”, meaning that virtual machines have different prices per click at different times. Amazon does this so as to run a number of virtual machines at any moment in the day that call on the processing capacity of their cloud in the best possible way.

3.2.2 Make it attractive for the (internal) end-customer to purchase green services.

The Total Cost of Ownership (TCO) of ICT is an important pricing metric that is used to indicate the ICT costs (efficiency) per ICT service or resource, and also to calculate business cases in ICT organisations. At the moment, this cost metric is of a financial nature and all the costs incurred for procurement, scrapping, use, and management of ICT are all simply lumped together in the same category. Greenness is normally not included.

To return to the previous point about making greenness transparent: it is important to refer in reports explicitly to the greenness components of TCO, for example emissions. Given that emissions by ICT can be converted into emission rights – when the present report was drawn up the standard price of emission rights was 13–15 euros per ton of CO2 – emissions can be counted as part of TCO so as to

arrive at a “green” figure for TCO. Another and probably better incentive is to include total energy consumption (of the entire cloud chain) in de TCO; energy is, after all, more expensive than the associated emissions.

3.3 How can the design and practical implementation of ICT be made green?

This section discusses measures that can make the design and practical implementation of ICT – and consequently of clouds – greener. This is not only relevant to a cloud provider but also to customers because they can benefit from greener (client) ICT.

The measures below were drawn up on the basis of research and recommendations from various sources. One model that includes many such

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measures in a single cohesive data centre-specific model is the OpenDCME model.11 That model examines various different aspects of a data centre; it can be used both to determine the maturity of those aspects and also to improve them. The EU has also drawn up a Code of Conduct for Data Centres that prescribes many of these measures.12

Greenness criteria and measures are:

Provider Make use of virtualisation. Determine the extent of virtualisation.

Efficiency Provider Make use of efficient

scheduling and provisioning methods.

Check whether use is made of efficient scheduling and provisioning methods. Efficiency Provider, customer

Optimise the distance between customer and provider so as to balance network and transport consumption.

Weigh up different energy consumption scenarios (varying the location of the provider and the customer) in terms of ICT resources, network, and energy transport and make a choice. Effectiven ess Provider, customer • Use energy-efficient server hardware. • Use energy-efficient client hardware. • Use energy-efficient other resources.

Assess using OpenDCME, EU Code of Conduct for Data Centres, Energy Star, or similar standards and norms; choose which.

Effectiven ess

Provider Use sustainable energy. Use the Fuel Mix Label [stroometiket] when selecting an energy provider; take account of this when optimising the distance.

Carbon footprint

Provider Construct sustainable data centres.

Use BREEAM, LEED or similar standards/seals of approval; choose which.

Carbon footprint

3.3.1 Make ICT resources more efficient: virtualisation, efficient scheduling, and provisioning methods.

Improving the energy efficiency of the ICT resources by such means as virtualisation will generally lead to better utilisation of ICT sources.

3.3.1.1 Make use of virtualisation.

It is not only CPUs but also other components such as hard disks, memory, and network equipment that consume energy, meaning that even when a server seems

11_OpenDCME

http://www.opendcme.org

12_{EU Code of Conduct for Data Centres}

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to be idle, it may still be using up to 60% of its maximum capacity. One way of increasing the energy efficiency of data centres is to virtualise the servers, with each server being divided up into VMs (virtual machines). Utilising several VMs on a server is known as “server consolidation”; it means that fewer actual physical servers are necessary and that less energy is therefore consumed.13 Most – if not all – cloud providers are already using this technology: a cloud service without virtualisation is almost inconceivable.

3.3.1.2 Make use of efficient scheduling and provisioning methods.

Energy consumption can be reduced by means of methods or algorithms (dynamic provisioning algorithms) that select a small collection of active servers so that the other servers can be switched to a low power setting. There are all kinds of heuristics and algorithms for the energy-efficient scheduling of multiple tasks. This is often based on dynamic power management techniques such as DVFS (see for example footnotes 14and15). This method is only effective if it is worthwhile from the point of view of energy consumption to run servers at a lower utilisation level; in normal situations, efficiency requires the assumption that all servers need to be fully loaded.

3.3.2 Make ICT resources more effective: optimise distance, utilise energy-efficient hardware, other resources

Effectiveness can be influenced by making the ICT resources more energy-efficient as well as the other resources such as cooling, accommodation, external networks, and energy transport. Having energy-efficient ICT resources will reduce the energy consumption of the ICT resources as a whole, meaning that it will influence the energy consumption of other supporting resources such as cooling: if less heat is generated because the ICT resources consume less energy, then less cooling will also be necessary overall.

However, effectiveness is highly dependent on the location and efficiency of the cooling systems, meaning that the effectiveness improvement may perhaps be less than expected, thus leading to situations in which improving the energy efficiency of ICT resources can even lead to a higher PUE than in the existing situation.16 In order to prevent this, it is necessary to take a close look at the effectiveness of the cooling systems compared to the ICT resources (see below).

3.3.2.1 Optimise the distance between customer and provider so as to balance network and transport consumption.

The effective use of a cloud can be improved by improving the ratio between useful and non-useful energy consumption. What that in fact means is that the energy that is not utilised for ICT resources must be minimised.

The energy consumption of the network between the provider and the customer is considered to be non-useful. This means that storage and processing must take place at a location that costs the least energy. This requires both the distance and

13_{Energy-Efficient Cloud Computing, A. Berl et al., The Computer Journal, 2010.}

14_{Power-Aware Scheduling of Virtual Machines in DVFS-enabled Clusters, G. von Laszewski et}

al., Cluster Computing and Workshops, 2009.

15_{Energy Aware Consolidation for Cloud Computing, S. Srikantaiah et al., Microsoft Research,}

2008.

16_{Micro PUE. The Key to Data Center Energy Savings. A White Paper, R. Hunter and C.}

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the size of the ICT resources at specific locations to be optimised so as to control, for example, the network energy costs and the cost of transporting energy.

However, the energy consumption of the network is greatly dependent not only on the distance but also on how the network is used (see 3.2.1); that use is in turn dependent on the application or service that is ultimately constructed on the basis of an IaaS service. This means that it is only the customer for the IaaS service who can decide whether geographical distance is a significant factor in determining the energy consumption.

3.3.2.2 Utilise energy-efficient server hardware

Utilising energy-efficient server hardware has a direct influence on effectiveness but also on the ratio between the emissions generated during manufacturing/scrapping on the one hand and use on the other. A more energy-efficient server will shift the ratio more towards manufacturing/scrapping. The depreciation period for servers will need to depend not only on economic considerations but also on the point when the total carbon footprint needed to facilitate current and future utilisation is reduced by means of newer, faster, and more energy-efficient models.

There are various labels for ICT hardware that – to a certain extent – guarantee energy efficiency and low environmental impact, for example European TCO Certification17 and Energy Star.18 In 2009, the United States Environmental Protection Agency (EPA) produced version 1.0 of the Energy Star specifications for servers. Tests showed that replacing older servers with new Energy Star-labelled servers could reduce energy consumption by 30 to 50%.19

One limitation of the version 1.0 specifications is that they only give the requirements for small servers with a maximum of four processor sockets. Energy Star expects to bring out specifications for larger servers in the course of 2012. Measures or properties that ensure that a server is more energy-efficient include:

• Incorporation of advanced power management techniques, for example a low power or idling state when the server is hardly being used (or not used at all) and dynamic voltage and frequency scaling (DVFS), which allows the voltage and consequently also the energy consumption and speed to be altered. These techniques combined with effective scheduling methods (see below) bring about a reduction in energy consumption and therefore improved energy efficiency.

• Make use of blade servers,20 and enveloping blade chassis, with particular specifications, that take up less space and have greater potential for reducing energy consumption than normal rack servers, for example because the power supply can be shared.

Energy Star specifications are also being prepared for storage systems.

Using more efficient servers also reduces the amount of cooling required. Saving 1 Watt of energy consumption by a server can produce a saving of 1 to 2 Watts in consumption by the associated cooling system.

17_{http://www.tcodevelopment.com/} 18_{http://www.energystar.gov/} 19_{http://www.energystar.gov/ia/products/downloads/ES_server_case_study.pdf} 20 http://www.computable.nl/artikel/ict_topics/infrastructuur/2250799/2379248/blade-servers-waarheen-waarvoor.html

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3.3.2.3 Utilise energy-efficient client hardware

The energy efficiency of customers’ hardware is also capable of improvement. This is not really a measure relating to an IaaS-cloud but rather to services constructed on the basis of such a cloud. Given the energy consumption of servers vis-à-vis clients, clients – and related distributed hardware such as monitors, printers, and local office networks – account for a significant proportion of total energy consumption. Customers for cloud computing will therefore need to implement sustainable measures to reduce energy consumption. Replacing standard desktops by energy-efficient thin clients can reduce energy consumption by some 30%.21 Energy Star specifications have been published for energy-efficient thin clients.22

3.3.2.4 Utilise energy-efficient other resources

The following measures relate to other resources (at a data centre) and represent only a few of the possible measures in this field. They only apply if a cloud provider is in a position to construct its own data centre and therefore to influence how it is designed.

3.3.2.4.1 Utilise sustainable cooling systems

The energy needed to run cooling systems accounts for a considerable proportion – up to more than 50% – of the total amount consumed by a data centre.23 Minimising the energy consumption helps improve PUE-type metrics.

Traditional data centre cooling systems utilise CRAC (Computer Room Air Conditioner) units; these regulate the temperature, air pressure, and humidity by means of warm and cold flows of air through fans. There are various different types, with different levels of energy efficiency.Installing a central system rather than a number of independent CRAC units can bring about a major improvement in the system’s energy efficiency24. A related cooling system consists of CRAH (Computer Room Air Handler) units, which generally utilise cooled water. Chillers are water-cooling systems that produce cooled water for the ventilation units.

A number of metrics are available for measuring the efficiency of different cooling systems that are directly related to one another.24 25 All of them describe the ratio between the energy consumed and the heat removed. They are:

• Coefficient of performance (COP): the ratio between the quantity of heat removed (kW) and the electrical energy consumed (kW);

• kW/ton for chillers: the number of kW needed to remove a ton of heat; • Energy-efficiency ratio (EER) (for roof-mounted cooling systems).

In general, 0.6 kW/ton or less is taken to constitute good or very good energy efficiency for data centre cooling systems.

These metrics do not, however, provide full information regarding energy efficiency because the published values are calculated at a single point in time; actual

21_{Energy Efficiency in Thin Client Solutions, W. Vereecken et al., in: Networks for Grid}

Applications, 2010.

22_{http://www.eu-energystar.org/nl/database/?cmd=selectform;table=ce_thinclient}

23_{Best Practices Guide for Energy-Efficient Data Center Design, National Renewable Energy}

Laboratory, 2011.

24_{Electrical efficiency measurement for data centers, N. Rasmussen, 2007.} 25_{http://www.trs-sesco.com/converting_kw.pdf}

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efficiency will differ due to variation in the temperature outside. The location of the data centre also plays a role in the energy consumption of its cooling systems: a data centre located where the average temperature is lower will require less cooling.

The positioning of the cooling systems within the data centre is also very important for reducing energy consumption. Cooling systems positioned close to the servers will be more efficient than those that cool the whole space/rooms in the data centre, for example the traditional systems mentioned above. The metric indicated above does not therefore provide all the information needed to determine the level of efficiency: another important factor is how much heat needs to be removed in order to keep the servers at the required temperature; that quantity will be lower if the cooling systems are located closer to the servers. This is already possible with new, more sustainable cooling systems, for example liquid cooling, nano-fluid cooling, in-server, in-rack, and in-row cooling.26

3.3.2.4.2 Utilise certified energy facilities

The energy efficiency of electrical energy facilities is often given as a percentage that indicates what portion of the incoming energy has not been lost, for example when converting AC to DC using power supply units. The energy efficiency of such units depends on the load, and the number of circuits, and various other conditions. Units labelled as having 80% efficiency are not necessarily equally efficient: low loads in particular are generally least efficient. Power supply units with Energy Star certification have a guaranteed efficiency of 80% under any load.27

One of the main reasons for energy losses is the use of an uninterruptible power supply (UPS); it is therefore extremely important that this is energy-efficient. Energy Star certification is available for UPSs.28

3.3.2.4.3 Save on lighting

The lighting at data centres not only consumes energy, it also produces heat, which in turn leads to higher energy consumption by the cooling systems. Energy-efficient lighting will reduce the PUE. Energy efficiency can be achieved by installing timers, movement sensors, and energy-efficient light bulbs. The benefits of energy-efficient lighting are greater if the data centre is only partly occupied.29

3.3.3 Reduce the carbon footprint

The greatest benefits regarding the carbon footprint can be achieved by utilising sustainable energy and sustainable resources. Sustainable resources here means specifically data centres as buildings: efficiency improvement measures can be expected to already lead to a major overall reduction in the embedded carbon in ICT resources.

3.3.3.1 Utilise sustainable energy

It is perhaps stating the obvious, but the level of emissions caused by a kWh of sustainable energy is less than that resulting from a kWh generated by burning

26_{Green Cloud Computing and Environmental Sustainability, S. Garg and R. Buyya,}

http://www.buyya.com/Cloud-EnvSustainability2011.pdf, 2011.

27_{Green Cloud computing and Environmental Sustainability, S. Garg and R. Buyya, 2010.} 28_{http://www.energystar.gov/index.cfm?c=new_specs.uninterruptible_power_supplies} 29_{Guidelines for Energy-Efficient Datacenters, The Green Grid (}_{http://www.thegreengrid.org}_).

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fossil fuel. This means that the kind of electricity used needs to be taken into account. Every energy provider in the Netherlands is required to publish its “Fuel Mix Label” [stroometiket], which shows the level of emissions it produces per kWh.30 In 2010, 42% of Dutch electricity was “sustainable” and only a few providers (6 out of 25) supplied wholly sustainable energy; the choice of provider and its energy mix determines the ultimate level of emissions.

3.3.3.2 Construct sustainable data centres

The accommodation for data centre has a major potential impact on the environment, both during construction (for example depending on the use of sustainable materials) and during use (for example whether it is properly insulated). Measures in this regard only apply if a cloud provider is in a position to construct its own data centre.

There are various standards (under construction) that can be used to check whether the accommodation is sustainable. The BREEAM standard was developed in the United Kingdom as a sustainability seal of approval for various types of buildings; it applies to new buildings and to the extension or renovation of existing buildings. There is a specific sustainability seal of approval for data centres31, which considers, for example, the materials used to build them and the maintenance that they require. Utilising more sustainable materials will reduce the manufacturing/scrapping factor for greenness.

This seal of approval also considers direct energy consumption, with the PUE metric also being taken into account. It was developed specifically for the UK market but in the summer of 2011 the Dutch Green Building Council (DGBC)32 began developing a separate BREEAM-NL guideline for data centres (now available). This involves assigning points to metrics such as PUE that count in the assessment of data centres. A number of core groups and working parties worked to produce this beta version. With the assistance of NL Agency and in collaboration with market parties, DGBC now wishes to implement pilot projects to develop the beta version further for data centres.

A comparable standard for sustainable construction has been developed in the United States for commercial office buildings, namely LEED.33 A number of data centres have already been awarded the LEED seal of approval, but no specific version for data centres has yet been produced. A number of parties have produced a draft of a version of LEED for data centres.34

Our advice when new data centres are being constructed (or existing ones renovated) is to implement BREEAM or LEED standards and to have the building assessed.

30_{For an overview, see}_{http://www.groenestroomjagraag.nl/stroometiket}_. 31_{http://www.breeam.org}

32_{http://www.dgbc.nl} 33_{http://www.usgbc.org/leed}

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4 What specific steps must be taken?

The previous sections of this report dealt with what constitutes a green cloud and how a cloud can be made green. The factors and the measures are separate; the question is how they should be applied. The recommendations in the present section have been made from the perspective of the ICT-related roles of the purchaser of cloud services. It has been assumed that the purchaser is already prepared for or already utilises a cloud service; i.e. the decision as to whether to utilise in-house ICT or the cloud has already been made. It has also been assumed that the steps described in this section can guide the provider of the cloud service towards greener ICT.

4.1 Communicate about green

Besides the general measures that an organisation – whether provider or customer – will need to take regarding greenness, green awareness and transparency, it is important to focus and report on the carbon footprint. Two points are significant here:

1. Analyse the carbon footprint; and

2. Determine what carbon footprint metric is relevant.

4.1.1 Clarify the carbon footprint

This report shows that for ICT resources, the ratio between the operational carbon footprint on the one hand and the manufacturing/scrapping footprint on the other often “favours” the operational footprint. As a result, the greatest benefits can be achieved by minimising the operational component, i.e. by means of greater effectiveness and efficiency and lower emissions.

In order to focus on where efficiency, effectiveness and emissions benefits can be achieved, it is necessary to analyse the ICT resources utilised by both the provider and the customer and their carbon footprint. ComputaCenter has carried out a general “Green ICT” audit for the Greater London Authority and has made it available as a case study.5 As part of the case study, a measurement/estimate was carried out for both the embedded and the consumption component of the carbon footprint for each type of ICT resources. The figures are given in tabular form so as to clarify matters (Table 3). A distinction is made between office ICT resources and server ICT resources.

Table 3 - Carbon footprint of the GLA

Carbon footprint prior to virtualisation (kg CO2/year) %/year

Resource Embedd

ed Use Other Total

Embedd ed Use Other Desktops 37907 62248 100155 100155 38 62 0 Monitors 17505 19661 37166 37166 47 53 0 Laptops 4298 2031 6,329 6329 68 32 0 Printers 530 5389 5,920 5920 9 91 0 MFDs 49 924 973 973 5 95 0 Data centre 0 0 135725 135725 0 0 100 Servers 6682 135725 142408 142408 5 95 0

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Carbon footprint prior to virtualisation (kg CO2/year) %/year

Resource Embedd_ed Use Other Total Embedd_ed Use Other

Total 66973 225978 135725 428677 16 53 32

The conclusion of the study was that the greatest benefit came from virtualisation; Table 4 shows the potential saving for each measure.

Table 4 - Savings at the GLA

Emissions (kg CO2) in 2015/16

Measure Now Future CO_(%)2 saving Saving (%) Costs _(GBP) Saving (GBP/kg _CO

2) Thin clients 100155 33907 66,247 -66 55,440 0.84 MFD 6893 4649 2,245 -33 9,437 4.2 Video conferencing 83658 62406 21,212 -25 14,980 0.7 Virtualisation 142408 52222 90,186 -63 37,563 0.42 Hosting 135725 135725 - - - - Total 468839 288909 179,930 -38

The above-mentioned study is referred to as an illustration; it provides figures from a commercial perspective that can serve as the basis for deciding to utilise a cloud. In determining the greenness of a cloud chain between a provider and the customer, the carbon footprint must be determined for the provider, the customer, the network, and the energy transport.

4.1.2 Include the whole cloud chain

As we have seen, the carbon footprint for both the provider and the customer will need to be determined for a cloud chain. The whole chain will need to be analysed, from the provider to the customer and from the energy source (including transport costs) to the network. Where possible, explicit consideration must be given to the carbon footprint of the network connecting these two. The network is essential for a cloud; according to the factors in this report, it does not count as a useful ICT resource and yet it accounts for a significant portion of energy consumption. In practice, however, both the customer and the provider of cloud services purchase the network connection for fixed charges; as a result, the amount of energy consumed is unclear.

4.1.3 Determine what carbon footprint metric is relevant.

Metrics such as PUE and DCcE say little if they are utilised in an organisational context; in that context, concepts such as TCO are more comprehensible. Depending on the type of organisation, a metric for a cloud service customer will need to be selected that can specifically be converted into (financial) organisational targets and also in terms of efficiency, effectiveness, and/or emissions and embedded carbon. Examples:

• An ICT service provider applies carbon footprint per user; • A bank applies carbon footprint per transaction;

• A public authority applies carbon footprint per citizen;

• An educational institution applies carbon footprint per student.

Realistically speaking, the provider of an IaaS cloud can only report on the metrics that are relevant to its services (storage and processing), for example the carbon