RESEARCH ON A MODULAR ENERGETIC/CO2 ... ON A MODULAR ENERGETIC/CO2 ASSESSMENT MODEL OF ICT SERVICES...

RESEARCH ON A MODULAR ENERGETIC/CO2

ASSESSMENT MODEL OF ICT SERVICES

France Télécom Group copyrights

5 June 2012Sébastien SCHINELLA

PhD student Orange Labs, Paris Diderot – IPGP University

Didier Marquet

Senior Expert in Energy, Orange Labs(OLNC/RESA/DEAN/ECD), chairman ETSI EE/EE2, rapporteur UIT-T SG5/3 Q21 and Q19

Révised by Marc Aubrée

Ecodesign, Orange Labs(OLNC/RESA/DEAN/ECD), vice chairman EE/EEPS

CONTENT

� ENERGETIC AND ICT EVOLUTION CONTEXT

� LCA FRAME, WHICH PROBLEM AND POSSIBLE IMPROVEMENTS ?

� ON GOING RESEARCH AND PHD THESIS

– Presentation of modular energetic method

2 Copyrights France Telecom Group

– Principle of energy impact assessment

– Assessment example

– LCA study at the level of Silicon chip

– Example of Negative/Positive impact approach

� SOME PARADOX AND QUESTIONS

� CONCLUSION

Orange Labs – R & D

Assessment and Reduction of Energetic Impact of ICT services – 5 June 2012

ENERGETIC CONTEXT

AND ICT EVOLUTION

Orange Labs-R&D

AND ICT EVOLUTION

ICT CONTEXT AND EVOLUTION

Still far from physic/technical limits but is it sustainable to go further?

from Moore law till 2020 ? (1) (2) to Koomey law (4)

nb of MOS x 100clock in MHz

operation/kWh

4 Copyrights France Telecom GroupOrange Labs –R&DAssessment and Reduction of Energetic Impact of ICT services – 5 June 2012

� Today still far from min bit energy (kB*T*ln(2)*10-21 Joules) (3) BUT …

� Wirth law : hardware improvement without enough software improvement gives small benefit to user AND fast Obsolescence, Waste, and Energy over-consumption

(1) http://en.wikipedia.org/wiki/Moore's_law (2) http://news.cnet.com/New-life-for-Moores-Law/2009-1006_3-5672485.html

(3) Landauer 1961, mesurée le 8 Mars 2012 au CNRS/ENS Lyon(4) http://en.wikipedia.org/wiki/Koomey%27s_Law

TO GO SUSTAINABLE move from nb of transistors / cm² to sustainable services / Watt ?

ICT BROAD-BAND AND USAGE INCREASE, NOT ENOUGH SUSTAINABILITY

� According ITU-D 2011outlook, massive internet deployment (PC, net-portables,

smart phones and tablets)

� Global IP traffic X5 from 2008 to 2013 91% for Video (IPTV, VoD, P2P)

�� Could new BB services encourage more sustainability ?

Fast Deployment of BB

5 Copyrights France Telecom GroupOrange Labs – R&D


BBnet-terminals

400,0

500,0

600,0

700,0

800,0 Network

Datacenter

coax cables

internet

fixed

ADSL

Core sites

+ mngt in DC

mobile

Phone 3G

Mobile phone

+-10% WORLD ELECTRICITY CONSUMED BY ICT

CUSTOMER DEVICES DRIVE THE BIGGEST ENERGY INCREASES

234

74(TV: network not included)

TWh

NETWORK


0,0

100,0

200,0

300,0

400,0

World consumption of ICT

Terminals

Terminaux

PC portable

Fixed phones

box

TV

PC fixeSources : ITUSources : ITUSources : ITUSources : ITU----D data, D data, D data, D data, KoomeyKoomeyKoomeyKoomey datacenter assessment, datacenter assessment, datacenter assessment, datacenter assessment,

Orange Labs assessment: all with a huge uncertaintyOrange Labs assessment: all with a huge uncertaintyOrange Labs assessment: all with a huge uncertaintyOrange Labs assessment: all with a huge uncertainty

441CUSTOMER DEVICES

ENERGY CONSUMPTION MUST BE DRASTICALLY DIVIDED

USE PHASE :ICT Electricity use till 2030 (IEA 2010)


� Energy demand is increasing too fast in use AND also in manufacturing phase, so that there is no sustainable solution with fossil, nuclear or renewable energy.

� PEAK ALL imposes at first ENERGY/RESSOURCES SAVING and RECYCLING

There’s no way out

�We need a precise assessment/simulation tool to optimize ICT services energetic impacts and positive impacts on other sectors

Orange Labs –R&D


1. goal and

scope definition

WHICH FRAME FOR LIFE CYCLE IMPACT ASSESSMENT METHODS

� Our basis:

– General LCA standards ISO 14040, ISO 14044 for “goods”

– Adapted by ETSI (TS 103 199) and UIT-T (L1400, L1410 et L1420) for ICT

goods, network and services (GNS) and impacts of ICT on organizations,

projects and cities


2. life cycle

inventory4. life cycle interpretation

3. life cycle

impact assessment

Orange Labs – R&D


SOME IMPROVEMENTS REQUIRED ON EXISTING LCA METHODS

� According IDATE, French Energy/Environmental agency ADEME, research CNRS ECOTIC, LCA improvements could be:

– More open method and tools to avoid the “black boxes ”

– Method to detect and avoid huge errors in database or hypothesis

– More Modularity and thus Reusability

– Lighter LCA scenarii simulation and easier ICT optimization


– Lighter LCA scenarii simulation and easier ICT optimization

– Improvement of “Functional Unit” definition required for

heterogeneous network and for positive impact assessment

�� Research works have been started and have

already identified some solutions

Orange Labs –R&D


PHD THESIS

ASSESSMENT METHOD AND MODEL OF ENERGY/CO2 IMPACT OF ICT

SERVICE AND OF REDUCTION OF IMPACT IN OTHER SECTORS

� University Paris Diderot (Paris 7)-IPGP

– Thesis Director: Jean-Pierre FRANGI,


– Thesis Director: Jean-Pierre FRANGI,

– Thesis comity: Xavier CHAVANNE Paris 7, Alain ANGLADE (French

Energy Agency ADEME ) Didier MARQUET, Stéphane LE MASSON

Orange Labs,

� Method inspired from already recognized method for assessment of energetic process.Ex: Comparison of the energy efficiency to produce agroethanol between various industries and processes: Synthesis, X Chavanne et JP Frangi, 2011

Orange Labs – R&D


ASSESSMENT METHOD PRESENTATION

� The method will be presented on a case study

� 1- DEFINE GOAL AND SCOPE:

Compare 2 types of meetings in terms of energy/CO2 consumption but not comparable on many other aspects: The e-conference (Orange Service Coop-Net) and the physical meeting.

- The “C’N” is quantified by consumption rate in Whelec/C'N


- The “C’N” is quantified by consumption rate in Whelec/C'N

- The physical meeting consumption rate in Whelec/physical meeting or

kWhPCI/physical meeting

Some differences with LCA:

� We cannot apply exactly the same single FUNCTIONAL UNIT for energy/CO2 comparison. 2 independent rates must be defined.

Orange Labs – R&D


ICT AND PHYSICAL SERVICE BOUNDARIES AND HYPOTHESIS

– ICT Network boundaries for C’N :

ex of simplified architecture:

We only consider ICT device and their average consumption and traffic. We don’t

consider building/heating/light/furniture.

PCs + screen + access network

Core network Servers


– Physical meeting boundaries:

We only consider average use of transport energy, depending on distance (walk,

bikes, bus, cars, trains, planes). We don’t consider building, hotel, road, rails,

railway station, vehicule design and manufacturing. We assume it is negligeable

in first run, but this should be verified.

� In both case, for 1st approach, we don’t consider the people involved for design, operation and maintenance of the services: e.g. software developers or train staff

Orange Labs – R&D


BASIC STUDY OF INDEPENDANT OPERATIONS FOR A SERVICE

� The final SERVICE (C’N ) is decomposed in basic independent operations with energy input and operation output and so a defined consumption rate:

� oi and ei are choosen in order that:

MODULE of OPERATION i

Consumed Energy ei

Ex: Electricity flow in Wh at input

Output oi

Ex: data flow at a given speed in Gbri = ei / oi


� oi and ei are choosen in order that:

– Rule 1: oi must be the most characteristic of the operation (e.g. Gb)

– Rule 2: The energy consumption rate ri is defined to be the most invariant

as possible (like an efficiency over a range of load)

� DIFFERENCE with LCA: in LCA database, there is a consumption rate r but often

not characteristic enough of the output operation: Example the LCA consider

earphone in Wh/kg while the new method will use r =Welec/Wsound because sound

is the output not kg. Maybe kg of material (e.g. magnet) may appear but in deeper

steps of the analysis.Orange Labs – R&D


� For each operation i, we can define, a consumption rate Ri to provide the final

service unit S (C’N in the example) as:

Ri = ei / S (Ex : Whelec/qty of operation i used for unit of S)

� Ri can be calculated from ri using the weight of the operation i in the final service

(C’N) wi = oi / S= ri * wi

R1: Terminal

R2: Access network

Ri: Core network

…

HOW TO ASSESS THE FINAL SERVICE IMPACT BASED ON OPERATIONS

Dem: Ri = ri * wi = (ei / oi) * (oi / S) = ei / S


(C’N) wi = oi / S= ri * wi

wi may depend of many variables e.g. network quality, redundancy, security,

etc… on which it is essential to reduce uncertainty

� The SERVICE consumption is then a simple sum of operations consumptions:

R = Σ Σ Σ Σ Ri =Σ =Σ =Σ =Σ ri * wi

ADVANTAGES: simple comparison and optimization of each operation energy efficiency and wide possibility of simulation with (ri , wi, Ri)

Orange Labs – R&D June 2012


Dem: Ri = ri * wi = (ei / oi) * (oi / S) = ei / S

� Core network operation consumption rate:rcore network ≈ 0,85 Wh/Gb (Baliga J et al. 2010) in use phase on 800 km distance,

redundancy 1+1 (i.e. network load = 50%) and with PUE=1,5

� assessed error: δδδδr/r ≈ 100%

� Operation weight in C’N

– w ≈ = 0,84 Gb/C‘N = N (Gb/h /PC) * t * N with mean C’N

EXAMPLE OF AN OPERATION USE ENERGY ASSESSMENT :

The simplified core network MODULE


– wcore network ≈ = 0,84 Gb/C‘N = Nbit(Gb/hC'N/PC) * tC'N * NPC with mean C’N

values of 2009, wT = 0,108 * 1,37 * 5,7

� Impact rate R of core network operation in C’N service:

– R core network = r* w = 0,7 Wh /C'N

� assessed error: δδδδ R/ R ≈ 100% strong uncertainty but very low weight on the

global consumption of SERVICE 81 to 786 Wh/C’N so no need to go deeper in study

COMPARED TO LCA: Similar cut off simplification rules as LCA

Orange Labs – R&D


EXTENDED STUDY TO MORE DETAILED OPERATIONS

AND CONSIDERING INVESTMENT + OPERATIONAL

NETWORK

ri-NW

wi-NW

Ri-NW

ro-NW

wo-NW

Ro-NW

COMPUTER SCREEN IP PHONE

ONE END USER

+ +

ro-PC

wo-PC

Ro-PC

ri-screen

wi-screen

Ri-screen

ri-tel

wi-tel

Ri-tel

ro-screen

wo-screen

Ro-screen

ro-tel

wo-tel

Ro-tel

ri-PC

wi-PC

Ri-PC


NETWORK

OTHER END USER

AUDIO BRIDGE

SERVERSSWITCH &

FIREWALLS

DATACENTER

+ +

ri-AB

wi-AB

Ri-AB

ri-SFW

wi-SFW

Ri-SFW

ri-serv

wi-serv

Ri-serv

ro-AB

wo-AB

Ro-AB

ro-SFW

wo-SFW

Ro-SFW

ro-serv

wo-serv

Ro-serv

Orange Labs – R&D


AVERAGE SCENARIO ANALYSIS:

170

125

150

175

TOTAL : R = Σ Σ Σ Σ Ri = 370 Wh/(hconf.user)Normalized consumption to 1 h C’N & 1 user

to show critical parameters.us

er)

)

HYP: Lifetime PC and screen : 3 yearsUse time per year : 2000 hServers manage 582000 Coop'Net per year, of mean time 1.67 hwith 4.6 users in 2008Data Sources : LCA, Williams 2002, Williams 2004, Orange data


22

4.8 3.5 3.2 0.99.9

60

40

2.8 0.03

19

4.4

29

0

25

50

75

100

125

Computer Screen IP Tel Network Audio

bridge

Switch &

firewalls

ServersInvestment Operational

to show critical parameters

Rj(W

h/(

hc

on

f.u

se

r

Orange Labs – R&D


EXAMPLE OF PARAMETER SENSIBILITY

� Same PC and screen but lifetime X 2, (thus ri = ei/oi and Ri is divided by 2)

� Same other hypothesis

85100

125

150

175

TOTAL : R = 270270 Wh/(hconf.user)(previous = 370)

co

nf.u

se

r))


85

114.8 3.5 3.2 0.9

9.9

60

40

2.8 0.03

19

4.4

29

0

25

50

75

100

Computer Screen IP Tel Network Audio

bridge

Switch &

firewalls

Servers

Investment Operational

Rj(W

h/(

hc

on

f.u

se

r

Orange Labs – R&D


EXAMPLE OF SIMPLE SIMULATION OF DIFFERENT SCENARII WITH CHANGES OF PARAMETERS IN USE

PHASE

PCNetwor

kServer TOTALTOTAL

Standard PC and

PUE server = 1.8625 1 160 786

Tablet replaces PC 40 1 160 201

Direct consumption Wh / C’N


PUE = 1.3 625 1 113 739

Servers 5d/7 12h/24 625 1 56 682

Servers 5d/7 12h/24 + Tablet 40 1 56 97

PUE =1.3 + servers

5d/7 12h/24 + Tablet40 1 40 81

Orange Labs – R&D


DEEPER LEVEL OF ANALYSIS

TO REDUCE ERROR ON THE DOMINANT IMPACT

� The customer terminal (PC) dominates, especially manufacturing phase � more study required

Chips 55% PCimpact

Printed circuit

Passive

Quartz extraction

0.0006 %

Silicium purification

15 %

Lithograp 70 % of the

Chemical products 8 %

Tools cooling 9 %

Nitrogen production 6 %

Ultra-pure water 6 %

� Deeper inside Lithography (Hu 2008)

� Deeper inside PC factory (Williams

2004)

� Deeper inside Chip factory (Williams 2002)

20 Copyrights France Telecom GroupOrange Labs – R&D


Passive components

Hard disk 12%, 2nd

post

Other

PC assembly

Lithography

70 % of the chip fabrication

Chip assembly

15 %

Ultra-pure water 6 %

Compressed air 5 %

Clean air room Air conditionning

37 %

Tools 31 %

DIFFERENCE WITH LCA: in LCA the energy to manufacture a chip is an average value in J/cm² from hidden values of different chip manufacturers. The averaged value of today LCA is too imprecise because it does not account the nanometer chip manufacturing complexity AND it cannot be reused for new chip generation.

DETAILS STUDY ON CLEAN ROOM (CR) AIR CONDITIONING (1/2)

3 main parameters:

• Difference of

CleanRoom

RCF

To EA

VRCF

TCRwout

Tout

Functions : Dust Filtering

and cooling

Function: Extraction of polluted air


• Difference of temperature∆∆∆∆T = TCR – Tout

• Difference of absolute humidity:∆∆∆∆ωωωω = ωωωωCR – ωωωωout

• recirculation rate

rr = VMUA /VRCF

MUAwCR

TCR

VMUA

wout

Functions : Temp, humidity

Control and dust filtering

Orange Labs – R&D


� Very different values depending on external air (temperature, humidity, dust)

CLEAN ROOM (CR) AIR CONDITIONING (2/2)

51

9821

76

TOTAL : 550 WTOTAL : 550 WTOTAL : 550 WTOTAL : 550 Weeee////mmmmCRCRCRCR

²²²²

7621

83

140

170

51

76

820

200

990

7147


MUA – filteringMUA – temp controlMUA – humidity controlRCF – filtreringRCF – coolingEA

TOTAL: 360 WTOTAL: 360 WTOTAL: 360 WTOTAL: 360 Weeee////mmmmCRCRCRCR

²²²²

3283

Crolles (France, temperate climate)

rr= 0.15

TOTAL : 550 WTOTAL : 550 WTOTAL : 550 WTOTAL : 550 Weeee////mmmmCRCRCRCR

²²²²

Taiwan (hot and humid climate)

recirculation rate rr=0.15 TOTAL : 2200 WTOTAL : 2200 WTOTAL : 2200 WTOTAL : 2200 Weeee

////mmmmCRCRCRCR²²²²

820

Taiwanrr= 1.06

Orange Labs – R&D


POSITIVE ICT ENERGY IMPACT BY SUBSTITUTION

� Using energetic SERVICE impact assessment, a similar assessment is

done for the physical service e.g. transport (at order 1): Ex of results

(Chavanne et Marquet, IEEE Telescon 2009 or ITU-T ICT and climate

change Focus Group)

Poland

Poland


� Above 7 km in Norway (mix hydro) and 15 in Poland (mix coal) less primary energy consumed by using Coop'Net.

� In CO2, the thresholds are 1 km and 20 km

� BUT… rebound effects not considered: it would be of an order of 3

Coop'Net for physical meeting. neither parasitic effect: the PC used is also

used in physical meeting.

Norway Norway

Orange Labs – R&D


Some paradoxes and rebound effects(1865 Jevons - 1980 Khazzoom-Brookes)

Orange Labs-R&D

(1865 Jevons - 1980 Khazzoom-Brookes)

Paradox, rebound, parasite… how quantify?

� Parasites consumptions

– 33 TWh spams = 10 x Orange conso (Mac Affee) and more “on” time, memory

– Video, adds incrusted in web page = 55% traffic: more BB !!!

– Always ON services imposes hot standby « small gains are killed by standby »

(ADEME)

� Rebound effect and issues

– 100 to 1 substitution: Mails, did people receive 100 letters per day before?

– Do the user consume less in the time saved by ICT ?

Services Mosaic = more servers activated


– Services Mosaic = more servers activated (zapping)

– Consumer becomes producer (YouTube, etc.) �BB explosion

– Substitution or superposition of service ? Substitution ≠ Dematerialization: Digital picture + printer rather than silver photo

– paradox of EE equipment too fast replacement creates grey energy

� But some very strong positive indirect gains

– EXEMPLAR car sharing services

��Rebound effect true measurement of method" possible ( cf Sussex university), also TNO and Arcadis in IDATE 2009 comm and strategy

Orange Labs – R&D


Method Advantage and next step

� Method for service but can improve GNS LCA by more systematic approach with R, r and w

� Reduce error rate of Data Base by defining with expert the relevant operation consumption rate “r” : it avoids average value bias due to data confidentiality

� Determine clear modularity and reuse, simplifying sensibility study because it is transparent and deterministic,


� Impact coefficients in SERVICE consumption allow Native EE simulation optimization

� Next step is better rate determination for equipment and software and work on positive impact

� At long run, it could enable service label standards

Orange Labs – R&D


Thank you very much

Questions ?

Orange Labs-R&D

Questions ?

RESEARCH ON A MODULAR ENERGETIC/CO2 ... ON A MODULAR ENERGETIC/CO2 ASSESSMENT MODEL OF ICT SERVICES...

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