Koomey on Internet infrastructure energy 101
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Transcript of Koomey on Internet infrastructure energy 101
How green is the internet?
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Internet Infrastructure Energy 101 Jonathan Koomey, Ph.D.
Research Fellow, Steyer-Taylor Center for Energy Policy and Finance
Stanford University http://www.koomey.com
June 6, 2013
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Defining “the Internet”
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The big picture view
Source: Ericsson and TeliaSonera (Malmodin and Lundén et al 2013) with support from CESC, KTH Sweden
Key components
• Data centers • Core network • Access networks • End-user
communications equipment
• End-user computing equipment
Lots of complexity here! 4
The Internet is data…
Total data flows
1986
1993
2000
2007
Source: Adapted from Hilbert et. al. 2011
Mobile data
Fixed Internet
Voice
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…but it’s also physical
Photo sources (clockwise from top left): Google. Flickr users Mr. T in DC, digger_90_tristar, geerlingguy, alachia, antonionicolaspina 6
0 500 1000 1500 2000
IP core network
Operator activities
Access networks
Other user equipment
Data centers and LANs (3rd party)
User PCs
Electricity use, GWh/year
What matters most….
These are key
Source: Ericsson and TeliaSonera (Malmodin and Lundén et al 2013) with support from CESC, KTH Sweden. Data are for Sweden, circa 2010.
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The big three
End-user equipment
Data centers
Access networks
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End-user equipment
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End-user equipment Computing
– Desktops and local servers – Laptops – Tablets
Communications – Phones – Wireless routers – Set-top boxes – Switches
Display – Computer monitors – TVs (IP connected)
Ultra low-power computing/sensors (small but growing) Photo sources (clockwise from top left): Flickr users sucello, expertcomp, verdammtescheissenochmal, janitors
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Growing base of devices worldwide
Desktops and laptops Servers
Source: IDC 2013 Vernon Turner 11
A key computing trend…
Source: Koomey et. al. 2011
Mobile systems and sensors becoming widespread, driven by progress in computing efficiency (100x every decade)
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…led to the rise of tablets and mobile phones
Source: IDC (http://www.idc.com/getdoc.jsp?containerId=prUS24129713)
Tablet shipments = desktops in 2012!
Source: Hilbert and López 2012a and 2012b
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Embedded emissions from manufacturing
Source: Koomey et. al. 2013
0% 20% 40% 60% 80% 100%
Server (Mac Mini OS X server)
Laptop computer (Macbook Pro 13")
Smart Phone (iPhone5)
NAND Flash memory - 1 GB
Share of CO2 emissions
Production Operation
0 200 400 600 800 1000 1200 Life Cycle CO2 emissions (kg)
Percentage contributions Absolute emissions
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Data centers
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Data center electricity use worldwide
Source: Koomey 2011. Graph shows worldwide numbers. For the US, the range for data centers in 2010 was 1.7 to 2.2% of the total. N.B. Infrastructure in this slide refers to cooling, fans, pumps, and power distribution inside data centers. 16
Data center lessons
Big inefficiencies in “in-house” data centers (cloud providers much better) Just adopting best practices will save 50+% Biggest impediments to efficiency are institutional, not technical IT efficiency most important, followed by infrastructure efficiency and sourcing of low-carbon electricity
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Access networks
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Access network bandwidth installed worldwide in 2010
Source: Hilbert and López 2012a and 2012b
- 500 1,000 1,500 2,000
2G mobile data Fixed line phone All mobile voice
Other 3G mobile data
2.5G mobile data Fiber
Cable Modem DSL
Installed capacity TB/second
0
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Source: Ericsson and TeliaSonera (Malmodin and Lundén et al 2013) with support from CESC, KTH Sweden.
0 50 100 150 200
Fixed cable-TV and fiber broadband
Fixed xDSL broadband
3G (WCDMA)
PSTN and VoIP
2G (GSM)
Electricity use, GWh/year
Access network electricity use (Sweden 2010)
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System effects of IT
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System effects of IT
Dematerialization (move bits, not atoms) – CDs vs. downloads
Big-systems optimization
– Smart parking sensors reduce traffic Enabling structural change
– Flatter, more nimble organizations
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Dematerialization: Move bits not atoms
Source: Weber et. al. 2010
CO2 emissions for downloads and physical CDs
-80% -40%
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Big systems optimization: Smart parking
Source: Mark Noworolski, Streetline Networks
Motes use <400µW on Average. For LA, with 40,000 parking spots, that implies total mote power of about 15W. Mote technology is from Dust Networks
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IT enables “business process redesign”, improving efficiency across the board. Example:
– Gave suppliers access to POS and inventory data, as well as company forecasts
– Pioneered aggressive use of RFID – Improved the flow of supplies and finished goods – The result: better coordination of suppliers with Walmart’s needs, plus much lower distribution costs
Structural change
For details on the Walmart example, see Traub 2012. For more examples, see Brynjolfsson and Hitt 2000. 25
Key research issues
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Key research issues
Need recent data on electricity use and potential savings Need more and better automated reporting of
– Energy use – User behavior
Average (fixed) vs. marginal (variable) energy use
– Most devices have high fixed energy use – Be careful to distinguish average vs. marginal effects
Need more system efficiency case studies 27
Conclusions
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Conclusions
Popular preoccupation with electricity used by Internet-related systems is misplaced
– Probably < 10% of total electricity but not well characterized – End-user devices important, but most can’t be clearly allocated to “the Internet”
System effects potentially much more important than direct electricity use
– IT affects efficiency in the other 90% of electricity use plus all the fuels
Updated data needed! 29
References
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References Brynjolfsson, Erik, and Lorin M. Hitt. 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance." Journal of Economic Perspectives. vol. 14, no. 4. Fall. pp. 23-48.
Hilbert, Martin, and Priscila López. 2011. "The World's Technological Capacity to Store, Communicate, and Compute Information." Science. vol. 332, no. 6025. April 1. pp. 60-65.
Hilbert, Martin, and Priscila López. 2012a. "Info Capacity| How to Measure the World’s Technological Capacity to Communicate, Store and Compute Information? Part I: Results and Scope." International Journal of Communication. vol. 6, pp. 956-979. [http://ijoc.org/ojs/index.php/ijoc/article/view/1562/742]
Hilbert, Martin, and Priscila López. 2012b. "Info Capacity| How to Measure the World’s Technological Capacity to Communicate, Store and Compute Information? Part II: Measurement Unit and Conclusions." International Journal of Communication. vol. 6, pp. 936-955. [http://ijoc.org/ojs/index.php/ijoc/article/view/1563/741]
Koomey, Jonathan. 2008. "Worldwide electricity used in data centers." Environmental Research Letters. vol. 3, no. 034008. September 23. <http://stacks.iop.org/1748-9326/3/034008>.
Koomey, Jonathan G., Stephen Berard, Marla Sanchez, and Henry Wong. 2011. "Implications of Historical Trends in The Electrical Efficiency of Computing." IEEE Annals of the History of Computing. vol. 33, no. 3. July-September. pp. 2-10. http://www.computer.org/csdl/mags/an/2011/03/man2011030046-abs.html
Koomey, Jonathan. 2011. Growth in data center electricity use 2005 to 2010. Oakland, CA: Analytics Press. August 1. http://www.analyticspress.com/datacenters.html
Koomey, Jonathan G., H. Scott Matthews, and Eric Williams. 2013. "Smart Everything: Will Intelligent Systems Reduce Resource Use?" In press at The Annual Review of Environment and Resources. May.
Masanet, Eric, Arman Shehabi, and Jonathan Koomey. 2013. "Characteristics of Low-Carbon Data Centers." In press at Nature Climate Change. May.
Malmodin, Jens, Dag Lundén, Åsa Moberg, Greger Andersson, and Mikael Nilsson. 2013. "Life cycle assessment of ICT networks–carbon footprint and operational electricity use from the operator, national and subscriber perspective." Submitted to The Journal of Industrial Ecology. March 8.
Traub, Todd. 2012. "Wal-mart used technology to become supply chain leader." In Arkansas Business. July 2. [http://www.arkansasbusiness.com/article/85508/wal-mart-used-technology-to-become-supply-chain-leader]
Weber, Christopher, Jonathan G. Koomey, and Scott Matthews. 2010. "The Energy and Climate Change Impacts of Different Music Delivery Methods." The Journal of Industrial Ecology. vol. 14, no. 5. October. pp. 754–769. [http://dx.doi.org/10.1111/j.1530-9290.2010.00269.x]
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