Quantitative Measurement of the Digital Divide

1
Quantitative Measurement of the Digital Divide

• Prepared by Les CottrellSLAC with Shahryar
  KhanNIIT
• http//www.slac.stanford.edu/grp/scs/net/talk07/ap
  s-apr07.ppt

2
Outline

• Why does it Matter
• How do we measure it?
• What is it telling us?
• RTT, Unreachability, Losses, Jitter, VoIP,
  Throughput
• Other Information
• Routing in Developing Countries
• Costs of Internet
• Comparisons with Development Indices
• Conclusions
• Acknowledgements, more information

3
Why Does it Matter

• 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.

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

• 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

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PingER Methodology
Uses ubiquitous ping
gtping remhost
Remote Host (typically a server)
Internet
Monitoring host
10 ping request packets each 30 mins
Once a Day
Ping response packets
Data Repository _at_ SLAC
Measure Round Trip Time Loss
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PingER Deployment

• PingER project originally (1995) for measuring
  network performance for US, Europe and Japanese
  HEP community
• Extended this century to measure Digital Divide
• Collaboration with ICTP Science Dissemination
  Unit http//sdu.ictp.it
• ICFA/SCIC http//icfa-scic.web.cern.ch/ICFA-SCIC/
  

• gt120 countries (99 worlds connected population)
• gt35 monitor sites in 14 countries

• Monitor 44 sites in S. Asia

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World Measurements Min RTT from US

• Maps show increased coverage
• Min RTT indicates best possible, i.e. no queuing
• gt600ms 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
2006
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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

SE Asia
L America
M East
C Asia
Oceania
S Asia
SE Europe
Russia
Developing Regions
Africa
E Asia
Developed Regions
US Canada
Europe
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Losses

• Mainly distance independent
• Big impact on performance, time outs etc.
• Losses gt 2.5 have big impact on interactivity,
  VoIP etc.

• N. America, Europe, E. Asia, Oceania lt 0.1
• Underdeveloped 0.3- 2 loss, Africa worst.

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Jitter

• Distance independent
• Calculated as Inter Packet Delay Variation (IPDV)
• IPDV Dri Ri Ri-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

Usual division into Developed vs Developing
Trendlines for IPDV from SLAC to World Regions
C Asia
S. Asia
Russia
Africa
SE Asia
L. America
M East
Australasia
Europe
N. America
E. Asia
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VoIP MOS

• Telecom uses Mean Opinion Score (MOS) for quality
• 1bad, 2poor, 3fair, 4good, 5excellent
• 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)

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
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World thruput seen from US
Throughput 1460Bytes / (RTTsqrt(loss)) (Mathis
et al)
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
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Normalized for Details

• Note step changes
• Africa v. poor
• S. Asia improving
• N. America, Europe, E Asia, Oceania lead

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Routing

• Between developing countries often use
  transcontinental links (like Europe in 80s),
  e.g.
• Pak to Pak or India to India is direct, however,
• Between Pak India via US or Canada or Europe
• Between India or Pak and Bangladesh via US or UK
• From S. Africa to African countries only Botswana
  and Zimbabwe are direct
• Most go via Europe or USA
• Wastes costly transcontinental bandwidth
• Need International eXchange Points (IXPs)

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Costs compared to West

• Sites in many countries have bandwidthlt US
  residence
• 10 Meg is Here, www.lightreading.com/document.as
  p?doc_id104415

• Africa 5460/Mbps/m
• W Africa 8K/Mbps/m
• N Africa 520/Mbps/m
• Often cross-country cost dominates cf.
  international

1 yr of Internet access gt average annual income
of most Africans, Survey by Paul Budde
Communnications
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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 (gt100 times
  worse)

Monitored Country
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Development Indices

• The size of the Internet infrastructure is a good
  indication of a country's progress towards an
  information-based economy.
• Measuring numbers of users not easy in developing
  countries because many people share accounts, use
  corporate and academic networks, or visit the
  rapidly growing number of cyber cafés,
  telecentres and business services.
• Furthermore, number of users does not take into
  account the extent of use, from those who just
  write a couple of emails a week, to people who
  spend many hours a day on the net browsing,
  transacting, streaming, or downloading.
• New measures of Internet activity are needed to
  take these factors into account.
• Most of the Internet traffic in a developing
  country is international (75-90)
• We measure international Internet performance
  which is an interesting (good?) indicator.

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Development Indices

• There are many development indices today
• UNDP Human Development Index (2006, 177
  countries)
• UNDP Technology Achievement Index (2001, 72
  countries)
• ITU Digital Access Index (2003) and the Digital
  Opportunity Index (2006), both 180 countries
• World Economic Forums Network Readiness Index
  (2004, 2005, 2006-2007 122 countries)
• Harvard University Network Readiness Index (2002,
  75 countries)
• Values 0 1.
• Typically some subset of GDP/capita, knowledge
  (e.g. tertiary education enrollment), life
  expectancy, network (hosts/capita, access,
  policy, usage, affordability, users/capita)
  technology (patents, royalties, exports,
  phones/capita, electricity)

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How do they Look?

• The indices show very similar behaviors world
  wide.
• Developed countries (US, Canada, Europe, E.Asia
  (jp, kr, tw), Australia/NZ, have high DOI
• Most of Non-Mediterranean or Southern Africa have
  poor DOI
• Land-locked countries plus Somalia, Tanzania,
  Myanmar, Iraq, Afghanistan have poor DOI
• Example DOI

Digital Opportunity Index from ITU, 2005
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UNDP 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 gross enrolment
  ratio (with one-third weight)
• A decent standard of living, as measured by GDP
  per capita.

Africa
PingER - Strong Correlation - Non subjective -
Quicker / easier to update
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Med. Africa vs HDI

• N. Africa has 10 times poorer performance than
  Europe
• Croatia has 13 times better performance than
  Albania
• Israel has 8 times better performance than rest
  of M East Med. Countries

• 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

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Digital Access Index (DAI)
infrastructure, affordability, knowledge and
quality and actual usage of ICTs

• Most European countries gt 1500 Kb/s throughput
  and greater than 0.6 DAI. Exceptions
• Malta, Belarus and Ukraine.
• Balkans is catching up with Europe, exception
  Albania is way down.

• E. Asia apart from China clusters
• M East Israel Cyrus close to Europe, Iran way
  down
• SE Asia 3 cluster Singapore at top, Malaysia and
  Brunei middle, Vietnam Indonesia at bottom
• S. Asia 2 clusters
• India, Pakistan, Sri Lanka
• Bangladesh, Bhutan, Nepal
• Africa at bottom
• Correlation strong

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DAI vs. Thru S. Asia

• More details, also show populations
• Compare S. Asia with developed countries, C. Asia

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Network Readiness Index (NRI)

• Ability to participate in and benefit from ICT
  developments
• environment for ICT offered by a country or
  community
• readiness of the community's key stakeholders
  (individuals, business and governments)
• usage of ICT among these stakeholders.

• Very similar to TAI (not shown) and DAI.

Strong correlations
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Conclusions

• World divides into developed vs developing
  regions
• Lots of variation within regions
• Last mile problems, and network fragility
• Decreasing use of satellites, expensive, but
  still needed for many remote countries in Africa
  and C. Asia
• Performance affects ability to collaborate
• Africa 10 years behind and falling further
  behind, leads to information famine
• E. Africa factor of 100 behind Europe
• Internet performance correlates strongly with
  development indices (linear for more technology
  based indices)
• Objective, relatively easy to measure regularly
• Need to increase coverage of monitoring to
  understand Internet performance
• Need support

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More information/Questions

• Acknowledgements
• Harvey Newman and ICFA/SCIC for a raison detre,
  ICTP for contacts and education on Africa, Mike
  Jensen for Africa information, NIIT/Pakistan,
  Maxim Grigoriev (FNAL), Warren Matthews (GATech)
  for ongoing code development for PingER, Connie
  Logg (SLAC) and David Martin (IBM?) for earlier
  developments, USAID MoST/Pakistan for development
  funding, SLAC for support for ongoing
  management/operations support of PingER
• PingER
• www-iepm.slac.stanford.edu/pinger,
  sdu.ictp.it/pinger/africa.html,
  www-iepm.slac.stanford.edu/pinger/pingertech.html
  
• Case Studies
• https//confluence.slac.stanford.edu/display/IEPM/
  Sub-SaharaCaseStudy
• https//confluence.slac.stanford.edu/display/IEPM/
  SouthAsiaCaseStudy
• http//sdu.ictp.it/lowbandwidth/program/case-studi
  es/index.html