Koomey on Internet infrastructure energy 101
 

Koomey on Internet infrastructure energy 101

on

  • 1,162 views

This talk, given at Google on June 6, 2012, summarizes what we know about energy use and information technology in a clear and understandable way. The person preceding me on stage was former Vice ...

This talk, given at Google on June 6, 2012, summarizes what we know about energy use and information technology in a clear and understandable way. The person preceding me on stage was former Vice President Al Gore, so the pressure was on! I think I delivered, but you be the judge.

Statistics

Views

Total Views
1,162
Views on SlideShare
1,162
Embed Views
0

Actions

Likes
1
Downloads
7
Comments
0

0 Embeds 0

No embeds

Accessibility

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Koomey on Internet infrastructure energy 101 Koomey on Internet infrastructure energy 101 Presentation Transcript

  • How green is the internet? 1  
  • 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 2  
  • Defining “the Internet” 3  
  • 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 5  
  • …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. 7  
  • The big three End-user equipment Data centers Access networks 8  
  • End-user equipment 9  
  • 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 10  
  • 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) 12  
  • …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 13  
  • 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 14  
  • Data centers 15  
  • 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 17  
  • Access networks 18  
  • 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 19  
  • 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) 20  
  • System effects of IT 21  
  • 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 22  
  • Dematerialization: Move bits not atoms Source: Weber et. al. 2010 CO2 emissions for downloads and physical CDs -80% -40% 23  
  • 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 24  
  • 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 26  
  • 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 28  
  • 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 30  
  • 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] 31