1. 1 1 Measuring the Digital Divide Les Cottrell – SLAC Lecture # 4 presented at the Workshop on Scientific Information in the Digital Age: Access and Dissemination ICTP, Trieste, Italy October, 2009 www.slac.stanford.edu/grp/scs/net/talk09/ictp-divide.ppt

2. 2 Summary The Digital Divide world wide, measurements Case Study of Africa Africa directions –Wireless/fibre, Routing, Costs, Difficulties, Conclusions & further information

3. Factors Earnings/poverty Age Rural vs City Education/skills Developed vs Developing regions –Policies, corruption, conflict, disease, protectionism, infrastructure (e.g. now power) 3

4. Where is it (country) Cartogram perspective see www.geog.qmw.ac.uk/gbhgis/conference/ cartogram.html www.geog.qmw.ac.uk/gbhgis/conference/ cartogram.html 4 Population Internet Users 2002 Area Tertiary Education from http://www.worldmapper.org/

5. 5 Measuring the Divide Worldwide Abv.NameOrganizationCountries Date of Data GDP Gross Domestic Product per capita CIA 2292001-2006 HDIHuman Development IndexUNDP1752004 DAIDigital Access IndexITU 180 1995-2003 NRINetwork Readiness Index World Economic Forum 1202007 TAITechnology Achievement IndexUNDP721995-2000 DOIDigital IndexITU1802004-2005 OIIndexITU1391996-2003 CPICorruption Perception Index Transparency Organization 1802007 5 Choose most: up-to-date, countries, important factors HDI & DOI

6. E.g.:Human Development Index(HDI) A long and healthy life, as measured by life expectancy at birth Knowledge, as measured by the adult literacy rate (with two-thirds weight) and the combined primary, secondary and tertiary education gross enrollment ratio (with one-third weight) A decent standard of living, as measured by GDP per capita (or Purchasing Power Parity (PPP) in US$). 6 1980 19902007 2000 Argentina gets worse in 90’s, S. America improves in 00’s, Africa improving long way behind

7. E.g. Digital Opportunity Index (DOI) Based on 11 indicators in 3 groups: Opportunity, Infrastructure and Utilization: Ideally DOI=1 –All homes have ICT devices, all citizens have mobile ICT devices, everyone using broadband, everyone access to ICT at affordable prices 7

8. 8 One way to measure (PingER) Behind Europe 5 Yrs: Russia, Latin America, Mid East 6 Yrs: SE Asia 9 Yrs: South Asia 12 Yrs: Cent. Asia 16 Yrs: Africa Central Asia, and Africa are in Danger of Falling Even Farther behind In 10 years at the current rate Africa will be 1000 times worse than Europe Derived throughput ~ 8 * 1460 /(RTT * sqrt(loss)) Mathis et. al 1993

9. 9 Some Other World Views Voice & video (de-jitter) Network & Host Fragility Data Transfer Capacity

10. 10 World Measurements: Min RTT from US Maps show increased coverage Min RTT indicates best possible, i.e. no queuing >400ms probably geo-stationary satellite Between developed regions min-RTT dominated by distance - Little improvement possible Only a few places still using satellite for international access, mainly Africa & Central Asia 2000 2008

11. Loss 11 With TCP (>80% Internet traffic) recovery from loss can take several seconds, such delays make interactive use annoying to impossible. For non TCP multi-media traffic loss causes poor voice/video (VoIP/H323) above 1.5%,loss > 0.5% unacceptable for IPTV http://www.slac.stanford.edu/comp/net/wan-mon/tutorial.html#loss Africa by far worst region, 10-20 times worse than developed regions

12. Case Study Africa 12

13. 13 Africa is huge, diverse & dreadful access Hard to get fibre everywhere ~ 1B people, over 1000 languages,multi climates 13 Fibres Capacity From Telegeography

14. 14 Mediterranean. & Africa vs HDI There is a good correlation between the 2 measures N. Africa has 10 times poorer performance than Europe N. Africa several times better than say E. Africa E. Africa poor, limited by satellite access W. Africa big differences, some (Senegal) can afford SAT3 fibre others use satellite Great diversity between & within regions HDI related to GDP, life expectancy, tertiary education etc.

15. Sub-Saharan broadband cost off-scale 15 www.itu.int/ITU-D/ict/publications/idi/2009/index.html Source ITU

16. 16 African Situation Access to the internet is so desirable to students in Africa that they spend considerable time and money to get it. Many students surveyed, with no internet connection at their universities, resorted to private, fee-charging internet cafes to study and learn. www.arp.harvard.edu/AfricaHigherEducation/Online.html www.arp.harvard.edu/AfricaHigherEducation/Online.html Internet Café in Ghana School in a secondary town in an East Coast country with networked computer lab spends 2/3rds of its annual budget to pay for the dial-up connection. –Disconnects Heloise Emdon, Acacia Southern Africa 1 yr of Internet access > average annual income of most Africans, Survey by Paul Budde Communications Survey (IHY meeting Ethiopia in November ’07) of leading Universities in 17 countries (will repeat with more clarity): –Each had tens of 1000’s of students, 1000 or so staff –Best had 2 Mbits, worst dial up 56kbps –Often access restricted to faculty

17. Demo: ITCP Internet Weather for Africa www-iepm.slac.stanford.edu/pinger/africa- weather08.movwww-iepm.slac.stanford.edu/pinger/africa- weather08.mov 17

18. Demo Shows population=bubble area, y=throughput, x=RTT as a function of time Note –Improved performance & increase of coverage with time –Africa clusters towards long RTT and poor throughput (bottom left) and generally far worse than rest of world –African varies by countries (cf Egypt & Ethiopia) –Big variations year to year Correlate with DOI index (opportunity, infrastructure, usage) by mobile telephony, Internet tariffs, #computers, fixed line phones, mobile subscribers, Internet users)/population http://www-iepm.slac.stanford.edu/pinger/pinger-metrics-motion- chart.htmlhttp://www-iepm.slac.stanford.edu/pinger/pinger-metrics-motion- chart.html 18

19. Possible Attractions Large Population (~1 Billion) Youthful population Saturation of developed markets makes emerging markets interesting to business (Vital Wave) Leapfrog technologies (cell phones, wireless …) Mature Emerging Strategic Emerging Niche Emerging Longterm

20. 20 http://www.internetworldstats.com/ Africa Huge growth ~ 3x lower penetration than any other region huge potential market

21. 21 What is happening: Fibre GEO-Stationary satellite $/Mbps 300 -1000 x Fibre, severely bandwidth-constrained,high latency Up until July 2009 only one submarine Fibre Optic cable to Sub-Saharan Africa, no competition, costly & only W. Coast 2010 Football World Cup => scramble to provide fibre optic connections to S. Africa, both E & W Coast Multiple providers = competition E. Coast: Seacom & TEAMs landed Jul 2009, Seacom working

22. 22 Plans for New Sub-Sahara Undersea Cables to Europe and India by 2011 Seacom (7/09) EASSy (6/10) TEAMs (9/09) WACS (Q2/11) MaIN One (Q4/10) GLO1 (11/09) ACE (2011?) $ 650M$ 265M$ 82M$ 2B ?$ 865 M$ 150 M??? 13.7 kkm10 kkm4.5 kkm13 kkm14 kkm9.5 kkm12 kkm 1.28 Tbps1.4 Tbps0.12 – 1.2 Tbps3.84 Tbps2.5 Tbps?0.64 Tbps??? June 2009Q1/Q2 2010Sept. 20092010Q4 2010Q2 20092011  Ambitious plans are once again underway to better-connect Africa  The potential increase in capacity compared to now is 1000X  The issue is whether there is a sustainable market  ”People are buying 10-15 times their existing bandwidth. They can get that much for the same sort of cash they’re already spending” Herlighy, Seacom CEO http://manypossibilities.net/african-undersea-cables SAT3

23. 23 Impact: RTT etc. As sites move their routing from GEOS to terrestrial connections, we can expect: –Dramatically reduced Round Trip Time (RTT), e.g. from 700ms to 350ms – seen immediately –Reduced losses and jitter due to higher bandwidth capacity and reduced contention – when routes etc. stabilized Seacom live Thu Jul 23, ‘09 - reported by BBC & CNNBBCCNN 325ms Big jump Aug 1 ’09 23:00hr Median RTT SLAC to Kenya Bkg color=loss Smoke=jitter RTT improves by factor 2.2 Losses reduced Thruput ~1/(RTT*sqrt(loss)) up factor 3 720ms

24. 24 From ICTP, Trieste, Italy Even Bigger effect since closer than SLAC –Median RTT drops 780ms to 225ms, i.e. cut by 2/3rds (3.5 times improvement) Aug 2nd Seems to be stabilizing Still big diurnal changes

25. 25 Next Steps: Going inland Extend coverage from landing points to capitals and major cites Need fibre connections inland Central Northern Southern Connect up the rest of the sites & countries (UG, RW, ML..)

26. Other countries on Seacom Tanzania, also dramatic reduction in losses Uganda inland via Kenya, 2 step process Rwanda inland via UG & KE 3 steps Many sites still to connect SLAC to Uganda 1 direction, Aug 3 Both directions, Aug 15 Sep 27 SLAC to Tanzania SLAC to Kigali Inst of Education, Rwanda 720ms 320ms 22-25 Sep ‘09

27. Other Countries 27 750ms450ms SLAC to Angola Angola step mid-May, more stable Ethiopia Mar ’09, most measured hosts on GEOS Zambia half step Aug 20, 09 still trying on 2 nd step. Via Namibia & ZA Aug 20 SLAC to Zambia 1 direction Both directions? Mozambique May 2007 (via ZA) Malawi future probably via Mozambique South Africa since started measurements to it in Feb’05 Why does Haramaya in Dire Dawa have fibre connection before Addis Ababa the capital?

28. And… September 6 ’09 Glo-1 ubmarine cable landed in Lagos, Nigeria. This brings competition to the SAT3/WASC/ cable consortium.’Glo-1 ubmarine cable landed in Lagos, Nigeria In May 2010 the Main One cable will be landing on the West Coast of Africa, more competition.Main One cable All this adds up to factors of 2 or more times improvement in 1-2 years for many hosts in many African countries. Hopefully this will dramatically help the rate of catch up. 28

29. Beyond fibres reach ABUJA Africa's first communications satellite suffered an energy failure just 18 months after its launch - Nov. 2008ABUJA In areas where fibre connections are not available (e.g. rural areas), the main contenders appear to be: –wireless, e.g. microwave, cellphone towers, WiMax etc., –Low Earth Orbiting Satellites (LEOS) for example Google signed up with Liberty Global and HSBC in a bid to launch 16 LEOS satellites, to bring high-speed internet access to Africa by end 2010,Google signed up with Liberty Global and HSBC in a bid to launch 16 LEOS gigaom.com/2008/09/09/google-invests-in-satellite-based-internet-startup/ –and weather balloonsweather balloons www.internetevolution.com/author.asp?section_id=694&doc_id=178131& http://crossedcrocodiles.wordpress.com/2009/06/26/undersea-broadband- fiber-optic-cables-to-africa/http://crossedcrocodiles.wordpress.com/2009/06/26/undersea-broadband- fiber-optic-cables-to-africa/ Wireless mobility –then wireless (cell phone, wimax, LEOS…) –cell phone growth leads Internet growth by 4.5 years –failure just 18 months after its launch - Nov. 2008 29

30. Mobile Leapfrogs –landlines –PCs 30 Use: e-mail, research purchase products online, listings, maps traffic info, IM, searches, banking, news –Landlines, desktops

31. Need for NRENs & IXPs 31

32. 32 IXPs a Major Issue for African Internet International bandwidth prices are biggest contributor to high costs African users effectively subsidise international transit providers! Fibre optic links are few and expensive  reliance on satellite connectivity High satellite latency  slow speed, high prices Growth of Internet businesses is inhibited In 2003 10 out of 53 countries had IXPs More IXPs  lower latency, lower costs, more usage Both national and regional IXPs needed Also needed: regional carriers, more fibre optic infrastructure investment Need NRENs country ->region –Then international IXPs Internet A B IXP Américo Muchanga americo@uem.mz, americo@uem.mz 25 September 2005

33. 33 Routing Used to typically go through a satellite provider such as Newskies Now TZ, UG & KE go via London and Teleglobe & terrestrial fibre IXPs starting up, e.g. S. Africa direct to Namibia, Botswana, Mozambique Burkina Faso direct to Mali, Senegal, Benin Ubuntunet Alliance > GEANT Founders: Kenya, Malawi, Mozambique, Rwanda South Africa Joined by DRC, SD, TZ, UG S. Africa Burkina Faso

34. 34 Next Steps: Let’s get together Get leaders such as universities, academic establishments (teach the teachers) to get togeher to form NRENs for country Bargain for cheaper rates BW most expensive worldwide ($4K/Mbps) Then NRENS get together to create International eXchange Points (IXPs) –Avoid intercountry links using expensive intercontinental links via Europe and the US. From Broubecker Barry 2008

35. Need for alternate routes Effect of Mediterranean fibre cuts Dec 2008 confluence.slac.stanford.edu/dis play/IEPM/Effects+of+Mediterran ean+Fibre+Cuts+December+200 8confluence.slac.stanford.edu/dis play/IEPM/Effects+of+Mediterran ean+Fibre+Cuts+December+200 8 35 Kbits/s RTT SLAC to Oman 8:30am 19 Dec 0:00am 22 Dec

36. ’05 Karachi cuts Mar 14, Karachi Water & Sewage digs up fibre – down 3 hours Jun-Jul 12 day outage,huge loss of confidence & business – satellite b’up inadeqaute Effect varied by country 36 Previous cut Jan 31 st 2008

37. 37 Conclusions: The bad Poor performance affects data transfer, multi-media, VoIP, IT development & country performance / development DD exists between regions & countries, rural vs cities, poor vs rich, old vs young… Decreasing use of satellites, expensive, but still needed for many remote countries in Africa and C. Asia Last mile problems, and network fragility Current providers (cable and satellite) have a lot to loose –Many of these have close links to regulators and governments (e.g. over 50% of ISPs in Africa are government controlled) Africa worst by all measures (throughput, loss, jitter, DOI, international bandwidth, users, costs …) and falling further behind.

38. Conclusions: There is Hope World cup: international fibre access + competition LEOS Leapfrog last mile fixed wire with wireless Cheaper end points: OLTP, net computer, smart-phones Banding together of universities => leverage influence & get deals => NRENs => IXPs Users –E.g. Ubuntunet, Bandwidth Initiative Standards: –Harmonization of regulations country to country –Cheaper cell phone, can’t afford multiple technologies & frequencies Regulatory regimes becoming: – more open/transparent, less resistant to change 38 “The way we develop here in Africa will be different from the way the big nations developed. They grew up with computers. We are growing up with mobile phones. - Fritz Ekwoge”

39. PingER: African coverage Host monitored in ~50 of 60 countries (98.7% pop) 131 hosts monitored in Africa Cannot find hosts in Comoros, Eq. Guinea, Sao Tome, (while here added Chad, and a 2 nd host in Guinea) Yellow only 1 host (so could be anomalous, e.g. Libya) Need help for contacts: (cottrell@slac.stanford.edu) 39

40. 40 More Information Case Study: Fibre for Sub Saharan Africa, see –https://confluence.slac.stanford.edu/display/IEPM/New+E.+Coast+ of+Africa+Fibrehttps://confluence.slac.stanford.edu/display/IEPM/New+E.+Coast+ of+Africa+Fibre Mediterranean Fibre cuts: –https://confluence.slac.stanford.edu/display/IEPM/Effects+of+Fibre+Outage+thr ough+Mediterraneanhttps://confluence.slac.stanford.edu/display/IEPM/Effects+of+Fibre+Outage+thr ough+Mediterranean –https://confluence.slac.stanford.edu/display/IEPM/Effects+of+Mediterranean+Fi bre+Cuts+December+2008https://confluence.slac.stanford.edu/display/IEPM/Effects+of+Mediterranean+Fi bre+Cuts+December+2008 ITU/WIS Report 2006 & 2007 ( or Google: “WSIS Report 2007”) –www.itu.int/osg/spu/publications/worldinformationsociety/2007/report.htmlwww.itu.int/osg/spu/publications/worldinformationsociety/2007/report.html –www.itu.int/ITU-D/ict/publications/idi/2009/index.htmlwww.itu.int/ITU-D/ict/publications/idi/2009/index.html Higher Education in Sub-Saharan Africa –www.arp.harvard.edu/AfricaHigherEducation/Online.htmlwww.arp.harvard.edu/AfricaHigherEducation/Online.html PingER –www-iepm.slac.stanford.edu/pinger, sdu.ictp.it/pinger/africa.htmlwww-iepm.slac.stanford.edu/pinger sdu.ictp.it/pinger/africa.html –www.slac.stanford.edu/xorg/icfa/icfa-net-paper-jan09/www.slac.stanford.edu/xorg/icfa/icfa-net-paper-jan09/ Global Information watch: www.giswatch.orgwww.giswatch.org Need network contacts in Africa: cottrell@slac.stanford.edu

41. 41 Extra Slides

42. 42 Trends:Losses N. America, Europe, E. Asia, Oceania < 0.1% Underdeveloped 0.3- 2% loss, Africa worst. Mainly distance independent Big impact on performance, time outs etc. Losses > 2.5 % have big impact on interactivity, VoIP etc.

43. 43 ~ Distance independent Calculated as Inter Packet Delay Variation (IPDV) –IPDV = Dr i = R i – R i-1 Measures congestion Little impact on web, email Decides length of VoIP codec buffers, impacts streaming Impacts (with RTT and loss) the quality of VoIP Trendlines for IPDV from SLAC to World Regions N. America E. Asia Europe Australasia S. Asia Africa Russia L. America SE Asia C Asia M East Usual division into Developed vs Developing Jitter

44. 44 VoIP & MOS Telecom uses Mean Opinion Score (MOS) for quality –1=bad, 2=poor, 3=fair, 4=good, 5=excellent –With VoIP codecs best can get is 4.2 to 4.4 –Typical usable range 3.5 to 4.2 –Calc. MOS from PingER: RTT, Loss, Jitter ( www.nessoft.com/kb/50) www.nessoft.com/kb/50 –Africa & C. Asia not possible, S. Asia with patience OK MOS of Various Regions from SLAC Improvements very clear, often due to move from satellite to land line. Similar results from CERN (less coverage) Usable

45. 45 Leading Country Population Int'l BW Mbps Int'l BW / capita (bps) Internet Users Internet users/ 1000 capita BW (bps)/ Internet User DOI Rank Egypt82,073,660.00378446.105100000012.1842378490 South Africa43,743,316.00881.520.152101250023.1464870.61791 Senegal12,938,350.0077559.899193511.4956340049.6112 Cameroon18,569,348.001558.347165000.3500423846.2137 Nigeria139,070,856.001501.07863500002.5167428.571155 Kenya38,213,024.00113.392.9673800002.093531417.38164 Uganda31,621,980.001003.162480000.2529912500152 Burkina Faso14,866,133.00765.1123142380.957755337.83163 Cote d'Ivoire18,465,326.0055.423.0013137470.744484031.43144 Benin8,349,959.00475.628863960.765997348.34147 Niger13,364,797.00302.244731170.233229624.64179 Mozambique21,379,584.0018.50.8653250001.16934740169 Ethiopia78,697,922.00100.1271121550.15445822.707173 Namibia2,067,433.0094.3532190009.19014473.684109

46. 46 Scenario Cases 4. Sep 05, international fibre to Pakistan fails for 12 days, satellite backup can only handle 25% traffic, call centres given priority. Research & Education sites cut off from Internet for 12 days Heloise Emdon, Acacia Southern Africa UNDP Global Meeting for ICT for Development, Ottawa 10-13 July 3. Primary health care giver, somewhere in Africa, with sonar machine, digital camera and arrangement with national academic hospital and/or international health institute to assist in diagnostics. After 10 dial-up attempts, she abandons attempts to connect 1.School in a secondary town in an East Coast country with networked computer lab spends 2/3rds of its annual budget to pay for the dial- up connection. –Disconnects 2. Telecentre in a country with fairly good connectivity has no connectivity –The telecentre resorts to generating revenue from photocopies, PC training, CD Roms for content.

47. 47 Unreachability All pings of a set fail ≡ unreachable Shows fragility, ~ distance independent Developed regions US, Canada, Europe, Oceania, E Asia lead –Factor of 10 improvement in 8 years Africa, S. Asia followed by M East & L. America worst off Africa NOT improving US & Canada Europe E Asia C Asia SE Europe SE Asia S Asia Oceania Africa L AmericaM East Russia Developed Regions Developing Regions

48. 48 Throughput Derive from: Thru ~ 8 * 1460 _____________ (RTT * sqrt(loss))

49. 49 Note step changes Africa v. poor S. Asia improving N. America, Europe, E Asia, Oceania lead Norm_thru = thru * min_rtt(remote_region)/min_rtt(monitoring_region) Thru = 1460 / (RTT*sqrt(loss)) Mathis et. al Norm Thruput

50. 50 World thruput vs ITU-OI Behind Europe 6 Yrs: Russia, Latin America 7 Yrs: Mid-East, SE Asia 10 Yrs: South Asia 11 Yrs: Cent. Asia 12 Yrs: Africa South Asia, Central Asia, and Africa are in Danger of Falling Even Farther Behind

51. 51 Overall (Aug 06) ~ Sorted by Average throughput Within region performance better (black ellipses) Europe, N. America, E. Asia generally good M. East, Oceania, S.E. Asia, L. America acceptable C. Asia, S. Asia poor, Africa bad (>100 times worse) Monitored Country

52. 52 Bandwidth & Internet use Note Log scale for BW India region leader Pakistan leads bw/pop Nepal very poor Pakistan leads % users Sri Lanka leads hosts% Pakistan leads bw/pop Nepal, Bangladesh, Afghanistan very poor Bit/s

53. 53 DAI vs. Thru & S. Asia More details, also show populations Compare S. Asia with developed countries, C. Asia

54. 54 S. Asia Coverage Monitor 44 hosts in region. 6 Monitoring hosts Loss from CERN Min-RTT from CERN

55. 55 S Asia MOS & thruput Mean Opinion Score to S Asia from US Daily throughputs from US to S Asia Last mile problems Divides into 2 –India, Maldives, Pakistan, Sri Lanka –Bangladesh, Nepal, Bhutan, Afghanistan Usable RTT ms RTT NIIT to QAU Pak (1 week) Mo Tu WeTh Fr Sa Su weekend vs. w’day, day vs night = heavy congestion Pakistan

56. 56 Americas Cuba poor throughput due to satellite RTTs and high losses US & Canada lead

57. 57 OECD Broadband Graphic from San Jose Mercury, 11/22/07

58. 58 Subscribers /people Subscribers / 100 people OECD median=27+-0.7 ITU Africa 3.34+-3.1

59. 59 Satellites vs Terrestrial Terrestrial links via SAT3 & SEAMEW (Med & W. Africa) –monopoly bandwidth is sold for $4.5K-12K per Mbps/mo (only 5% used) –Equal satellite prices PingER min-RTT measurements from S. African TENET monitoring station Mike Jensen, Paul Hamilton TENET, S. Africa Normal Satellite $/Mbps 300-1000x fibre costs Only 14 of 49 Sub- Saharan countries have fibre NEPAD ‘04 University

60. 60 Divide within Divide: Africa Throughput Overall Loss performance is poor to bad Factor of 10 difference between Angola & Libya N Africa best, E Africa worst Big differences within regions In 2002, BW/capita ranged from 0.02 to over 40bps - a factor of over 1000 99 hosts 45 Countries

61. 61 Validation Many indices from ITU, UNDP, CIA, World Bank try to classify countries by their development –Difficult: what can be measured, how useful is it, how well defined, how changes with time, does it change country to country, cost of measuring, takes time to gather & often out of date, subjective –Typically use GDP, life expectancy, literacy, education, phone lines, Internet penetration etc. –E.g. HDI, DOI, DAI, NRI, TAI, OI.. In general agree with one another (R 2 ~0.8) Given importance of Internet in enabling development in the Information age some metrics we can measure: –International bandwidth –Number of hosts, ASNs –PingER Internet performance See if agree with development indices. –If not may point to bad PingER data or illuminate reasons for differences –If agree quicker, cheaper to get, continuous, not as subjective –Working to extend PingER coverage (120=>156 countries, 45 in Africa)

62. 62 Thru vs Int. BW Hard to get to countries (E. Africa, C Asia) Last mile not good (China) ’07 vs ’05 (Aus & NZ) Emphasize Internet deploy (Estonia) Host choice (Congo, Libya) Derive: thru ~ 8 * 1460 /(RTT * sqrt(loss)) Mathis et. al Good Correlation norm_thru = thru * min_RTT(rem_region) / min_rtt(mon_region)

63. 63 PingER vs Speedtest www.zdnet.com.au/broadband/results.htm –Application sends known amount of data between your computer and servers –Measures throughput saves results by country, ISP About 30 countries have <= 3 attempts Server in Aus. AU&NZ agree Absolute values agree Strong Correlation Africa (magenta) worst off

64. 64 Digital Opportunity Index (ITU 2006) 180 countries, recent (data 2005, announce 2006), full coverage 2004-2005, 40 leaders have 2001-2005 11 indicators (grouped into: opportunity, infrastructure & utilization) –(Coverage by mobile telephony, Internet tariffs, #computers, fixed line phones, mobile subscribers, Internet users)/population Worked with ITU to see if PingER can help. –Added countries 130>150 –Increase coverage

65. 65 Correlation Loss vs DOI Good correlation, Africa worst off

66. 66 Automate uploading etc. via Internet

67. 67 Broadband Subscribers www.telegeography.com

68. 68 SAT-3 Projects in progress (before soccer World cup in S. Africa) –EASSy complete end 2008, S. Africa to Port Sudan. Consortium members include most of the national telcos from the various East African nations, including Telekom South Africa, Telkom Kenya, Zanzibar Telecom, Uganda Telecom, TDM Mozambique, Djibouti Telecom, Sentech, Telecom Malagasy, Rwanda Telecom, and Botswana Telecom, with about a dozen other likely participants. –SEACOM (2009) – S. Africa to EU and IN, also lands in Mozambique, Madagascar, Tanzania, Kenya and UAE –TEAMS - Burundi, Kenya, Rwanda, Tanzania and Uganda. –UHURUNET and its terrestrial segment, UMOJANET capacity of 3.84 Terabits/sec, the undersea submarine cable is intended to link the entire continent of Africa, with the outside world including Europe, Brazil, India and the Middle East –UBUNTUNET (Cisco router in London, to connect GEANT)

69. 69

70. 70 SAT3

71. 71 Fibre Links Future –SAT-3 shareholders such as Telecom Namibia, which has no landing point of its own find it cheaper to use satellite Will EASSy follow suit? Another option to EASSy: since Sudan and Egypt are now connected via fibre, and the link will shortly extend to Ethiopia, there are good options for both Kenya and Uganda/Rwanda and Tanzania to quickly link to the backbones via this route SAT3 connects eight countries on the W coast of the continent to Europe and the Far East. Operating as a cartel of monopoly state-owned telecommunication providers, prices have barely come down since it began operating in 2002 Mike Jensen

72. 72

73. 73

74. 74 Costs compared to West Sites in many countries have bandwidth< US residence –“10 Meg is Here”, www.lightreading.com/document.asp?doc_id=104415 www.lightreading.com/document.asp?doc_id=104415 Africa: $5460/Mbps/mo –W Africa $8K/Mbps/mo –N Africa $520/Mbps/mo (IDRC study Jan 2005) 1 yr of Internet access > average annual income of most Africans, Survey by Paul Budde Communications (OECD 2.5%, US 1.45%) Bandwidth Initiative: Coalition of 11 African Universities (MZ, TZ, UG, GH, NG, KY) + four major US Foundations to provide satellite thru Intelsat at 1/3 cost ($7.3K/Mbps/m => $2.23K) OECD: median=$16/Mbps/mo Japan=$3.09/Mbps/mo OECD study on Broadband Nov 2007 Bandwidth in Africa is hundreds of times more expensive than in Europe or N. America

75. 75 Why Make Internet Measurements? In the Information Age Information Technology (IT) is the major productivity and development driver., particularly science & education Travel & the Internet have made a global viewpoint critical One Laptop Per Child (“$100” computer) –New thin client paradigm, servers do work, requires networking (Google: “Negroponte $100 computer”), driving Intel & AMD cheap net-books –Internet enabled cell phones (e.g. iPhone) –Enables “Internet Kiosk & Cafe” can make big difference So we need to understand and set expectations on the accessibility, performance, costs etc. of the Internet