Post on 11-Feb-2022
A Green InternetA Green Internet
Rod Tucker
ARC Special Research Centre for Ultra-Broadband Information Networks (CUBIN)
My Friends:Jayant Baliga, Kerry Hinton, Rob Ayre
Information Logistics and EnergyInformation Logistics and Energy
Metro/Edge Network
Core Network
Energy and the InternetEnergy and the Internet
Energy
In
Video Distribution
Network
Data Center
Access Network
Data
Out
• Greenhouse Impact• Energy-limited capacity bottlenecks (“hot spots”)
• OPEX
• Enabling energy efficiencies in other sectors
Why is Energy Important?
The Internet
Putting Things into ContextPutting Things into Context
“SMART 2020: Enabling the low carbon economy in the information age,”
GeSI, 2008 www.gesi.org
Information and Communication Technologies (ICT)
Global Emissions GtCo2
e
Global Emissions
Emissions
ICTOther
Business as Usual 2020
5% of total
GtCO2
e
2020 Abatements
SummarySummary
Estimating energy consumption of the Internet
Where is the energy consumed-
Core, metro, access network, data centres?
Information Logistics -
Cloud Computing
-
Travel Replacement-
Airmail vs. Internet
The Khazzoom-Brookes postulate
Caveat: “Making predictions is difficult –
especially about the future.”
EthernetSwitch
OLTSplitter
Cabinet
Metro/Edge NetworkCore Network
Network Energy ModelNetwork Energy Model
Edge Routers PON
Fiber
EDFA
Core Router
Optical cross connect
Video Distribution Network
Storage
ServerServer
Storage
Data Center
Fiber
Access Network
DSLDSLAM
Cu
OLT
SwitchONU
Cabinet
PtP
FTTN
DSLAM
Fiber
Cu
Broadband Network Gateways
Hot spots
Tier 1 Network
OversubscriptionOversubscription
Peak access rate sold to userM =
Average access rate
Oversubscription~ 3 Mb/s in 2009
~ 0.12 Mb/s in 2009
M = 25
2500
Pow
er (W
/use
r)
Baliga et al., 2008
0
20
25
5
Peak Access Rate (Mb/s)
15
100 20015050
10
Power Consumption of IP NetworkPower Consumption of IP Network
Total
Routers
Access (PON)SDH/WDM Links
Today’s Internet (~ 3 Mb/s)
2009 Technology
Oversubscription = 25
% o
f Ele
ctric
ity S
uppl
y
0.5
1.0
Traffic Growth = 40% p.a
2009 2020
Power Consumption in Access NetworksPower Consumption in Access Networks
Wave7 ONT-G1000i
Splitter GPON
PtP
Edge Node
Cisco 6513
Hitachi 1220
NEC AM3160
Cisco 4503
NEC VF200F6
TC Communications TC3300
Axxcelera
ExcelMax
Cabinet
Access N/W
FTTN VDSL2
Cu
Fiber
Fiber
Cisco uBR10012
RF Gateway Cisco DCP3000
HFCCu
RF Amp
Node
WiMAX
AxxceleraExcelMax BTS
Fiber
Hitachi 1220
Splitter
30
Peak Access Rate (Mb/s)
Pow
er P
er U
ser (
W)
1 10000
PtP
PON
100
20
10
10
32 Customers
M ~10
M = 1
M = 1
Power Consumption in Access NetworksPower Consumption in Access Networks
M = 1
PON FTTH is “greenest”
FTTN
WiMAXM= 10
20 users per sector
HFC
M= 10M= 1
M= Oversubscription
LowLow--Power States in User ModemsPower States in User Modems
“With implementation of this Code of Conduct,…
5.5 Millions tons of oil equivalent (TOE) will be saved per year.”
Off-State (W)
Low-Power State (W)
On-State (W)
ADSL-CPE 0.3 3.5 4.0
VDSL2-CPE 0.3 4.5 6.0
GPON ONU 0.3 5.0 9.0
PtP ONU 0.3 3.0 5.0
Extract:
EUROPEAN COMMISSIONDIRECTORATE -GENERAL JRCJOINT RESEARCH CENTREInstitute for the Environment and SustainabilityRenewable Energies Unit
Code of Conducton Energy Consumption of Broadband Equipment
Draft Version 3Issue 15 – 17 July 2008
Total
Access (PON)Routers
2.5 25 250 2500
Ener
gy p
er b
it (μ
J)
1.0
1000
0.01
10
0.1
100~1 μJ/b
WDM (Optical Fibre Trunk Links)
Peak Access Rate (Mb/s)
Network Network EnergyEnergy Consumption Consumption per Bitper Bit
~100 μJ/b
Ene
rgy
per b
it (n
J)
0.01
0.1
1
10
100
1000
OpticalAmp
PoSWDMTx/Rx
EthernetSwitch
CoreRouter
PONONU
(10 Mb/s)
Server
20092009
Energy per Bit in Network DevicesEnergy per Bit in Network Devices
Largest Routing System available today
Cisco CRSCisco CRS--1 Router1 Router
Buffers, 5%
Control Plane, 11%
Switch Fabric, 10% Power and Heat Management, 35%
I/O, 7%
IP Look-Up and Forwarding Engine,
32%
Linecard Chassis: 1.28 Tb/s, 13.6 kW
Switch Fabric Chassis: 8 kW Power consumption
Energy in Electronic Integrated CircuitsEnergy in Electronic Integrated Circuits
CMOS Gates
Cwire
⎡ ⎤= + ⎣ ⎦∑ ∑ 21Energy2gate wireE C V
=Power Energy x Bit Rate
CMOS ASICLinecard
Source: ITRS ’97-’06 Roadmaps
Switching Energy in CMOSSwitching Energy in CMOS
Moore’s Law: Number of transistors x 2 each 18 months
Sw
itchi
ng e
nerg
y E
s, J
10-20
10-18
10-16
10-14
2000 2010 2020
?
65
32
130
250
18
CMOS Feature size (nm)
40% decrease /18 months(40% efficiency gain p.a.)
Router Capacity GrowthRouter Capacity Growth
Based on G. Epps, CISCO, 2006
1
10
100
1000
10000
1994 1996 1998 2000 2002 2004 2006
X 19
93 P
erfo
rman
ce
2008
CRS-1 (~1.3 Tb/s,13.6 kW/rack)
12416 (~0.3 Tb/s/rack)
12016 (~80 Gb/s/rack)
Year
Moore’s law x 2/18 m
Router capacity x 2.5/18 m
CMOS energy efficiency 40% p.a.
2010
Router energy efficiency improving at 20% p.a. Neilson, JSTQE 2006
25000
Pow
er (W
/use
r)
% o
f Ele
ctric
ity S
uppl
y
Baliga et al., 2008
0
20
0.5
25
5
Peak Access Rate (Mb/s)
15
100 20015050
1.0
10
Effect of Efficiency GainsEffect of Efficiency Gains
Total
Routers
Access (PON)SDH/WDM Links
2020
Overall Technology Efficiency Improvement Rate
= 0% p.a
2500
Baliga et al., JLT, 2009
0
20
25
5
15
100 20015050
10
5% p.a
Overall Technology Efficiency Improvement Rate
= 0% p.a
20% p.aTarget
10% p.a
% o
f Ele
ctric
ity S
uppl
y
0.5
1.0
Effect of Efficiency GainsEffect of Efficiency Gains
2020Peak Access Rate (Mb/s)
Pow
er (W
/use
r)
•
Alternatives for complex PC
•
Sleep mode and fast “wake up”, adaptive modes of network and clients
•
Sleep mode
•
Adaptive control of components based on communication requirements
•
Adaptive sharing of content
•
Highly efficient power adaptive processing
•
Virtualization
Global Packet Core
Network
Global Packet Core
NetworkServers and Data Centres Application
Content ServerEfficient Clients
and home networks
Application
Content Server
Towards EnergyTowards Energy--Efficient NetworksEfficient Networks
After: Gladish
et al., ECOC 2008
•
Energy management solutions e.g. optical/electronic bypass
•
Content delivery networks (e.g. IPTV)
Access Network Access Network
Data CentersData Centers
1Koomey, 20082Revolutionizing Data Centre Efficiency—Key Analyses”McKinsey & Company, April 2008.
•
Data center electricity consumption is ~1% of the global total1
•
Energy consumption of data centers worldwide doubled between 2000 and 2006 2
•
Incremental US demand for data centre energy between 2008 and 2010 is the equivalent of 10 new power plants2
1 MW Data Center
“Burden factor”
of 1.8 to 2.5 for power consumption associated with cooling, conversion/distribution and lighting
Sources: EYP Mission Critical Facilities, Cisco IT, Network World, Customer Interviews, APC
0
10
20
30
40
50
Server Storage Network
50% 35% 15%
Energy Consumption in a Data CentreEnergy Consumption in a Data Centre
ICT Infrastructure Cooling
Conversion Loss
Lighting
Some typical issues/questions:
•
Wired vs. wireless broadband access
•
Can Cloud Computing save energy?
•
Renewable energy sources
•
Physical vs. Internet delivery of data
•
Can Internet Travel replacement save the planet?
•
Optimum design of Video on Demand systems
Information LogisticsInformation Logistics
Management of data, including, transport, storage, and processinManagement of data, including, transport, storage, and processingg
Core Network
Metro/Edge Network
OLTSplitter ONU
Fiber
EthernetSwitch
Edge Routers
Broadband Network Gateways
CoreRouter
OXC
Computer, Storage
Servers,Processors
StoragePublic Data Center
Cloud ComputingCloud Computing
Servers,Processors
StorageEnterprise Data Center
PON Access Network
Total Energy Consumption =
Energy/bit used in • Storage• Transport• Processing
XTotal number of bits
Cloud
•
Software-as-a-Service–
Stored on user’s computer with updates downloaded regularly
•
Service Bureau–
Most tasks done on lower end user machine, outsource the “big” jobs
•
Computing-as-a-Service–
Hosted and run on provider computer “farm” with data initially uploaded from user (Thin client model)
Can cloud computing save energy ?
Three Cloud Computing ScenariosThree Cloud Computing Scenarios
Metro/Edge Network
Service Center
Access Network
Computing Resource
Service Bureau – Hardware & Software
Here is my raw video footage
and edit commands
Mid-range Computers
Service BureauService Bureau
Metro/Edge Network
Service Center
Access Network
Computing Resource
Here is your DVD Image
Mid-range Computers
Service BureauService Bureau
Service Bureau – Hardware & Software
Energy Consumption of Service Bureau ModelEnergy Consumption of Service Bureau Model
Computer used for 20 hrs/week, plus some video encoding of ½ hour videos
Older Computer
Mid-range Computer
Low-end Computer & outsourcing
Transport energy dominates
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100 120
Number of Encodings per Week
Ave
rage
Pow
er C
onsu
mpt
ion,
W
Following the Sun and the WindFollowing the Sun and the Wind
•
Locate computing and storage resources near sources of renewable
energy
•
Move data to follow the sun and winds
•
Requires many orders of magnitude increase in a data transport capacity
•
Transport/efficiency trade-off
Making best use of renewable energy
Data by Airmail vs. Data by the InternetData by Airmail vs. Data by the Internet
Data by Airmail:
Melbourne Sydney
3x105
32-GB flash
drives
The Internet
103
kg CO2
Data by Internet:
1000 Gb/s for 24 hours
105
kg CO2
Cargo Jet
(24 hours)
2 μJ/b
20 nJ/b
107
GB
107
GB
Total
Access (PON)Routers
2.5 25 250 2500
Ener
gy p
er b
it (μ
J)
1.0
1000
0.01
10
0.1
100~1 μJ/b
WDM Links
Peak Access Rate (Mb/s)
Energy Consumption Energy Consumption per Bitper Bit
~100 μJ/b
Flash chips by Airmail
2 μJ/b
Using the Internet for Travel ReplacementUsing the Internet for Travel Replacement
Source: CISCO, 2008
Video Conferencing
Travel Replacement Travel Replacement ––
Greenhouse Impact (C0Greenhouse Impact (C022 ))
~500 kg/person return
2 X 1 Gb/s for 6 hours = 4 TB
~5 kg/person
Air Travel
Video Conferencing
Melbourne Sydney
Business Meeting
0.1
1
10
100
1,000
10,000
100,000
100 1 10 100 1000
Mb/s-hr
Dis
tanc
e tra
velle
d (k
m)
CarTrain
Plane
Tele-work
Travel
10
Gb/s-hr
Bitrate-Time Product
Bicycle
Daily work
Business Meeting in Sydney
RodRod’’s Telecommute Calculators Telecommute Calculator
The The KhazzoomKhazzoom--Brookes PostulateBrookes Postulate
D. Khazzoom
Energy Journal,10,1987, L. Brookes Energy Policy, 20,1992 Inhaber, “Why
Energy Conservation Fails”, Quorum, 2002H. Herring, http://technology.open.ac.uk/eeru/staff/horace/kbpotl.htm
•
Energy efficiency at micro level reduction of energy use at this level
•
But leads to an increase in energy use, at the macro level
•
Example:
Wide bodied passenger aircraft lower costs per passenger large increase in air travel increased greenhouse emissions
“Energy efficiency is absolutely the wrong approach to network design.
The objective should be to make the network carbon neutral”
-
Bill St. Arnaud, CANARIE
Some Interest Groups and OrganizationsSome Interest Groups and Organizations
http://www.gesi.org/
http://www.thegreengrid.org/home
http://www.itu.int/climate
http://wattwatt.com/
http://ictandclimatechange.com/
http://www.atis.org/0050/
•
Energy consumption of the Internet is small, but growing
•
Internet energy consumption dominated by–
Access network today
–
Core network in the future
•
A multi-faceted approach needed to build a green Internet:–
Improved efficiency in electronic and photonic devices
–
Low-energy switching techniques–
Improved architectures
–
New protocols
•
Information Logistics–
A new approach to network design and management
Summary Summary –– The Way ForwardThe Way Forward
Melbourne Information Logistics Centre (MILC)?
Centre for Information LOgistics (CILO)?