Transcript Quantitative Measurement of the Digital Divide Prepared by: Les CottrellSLAC with Shahryar KhanNIIT http://www.slac.stanford.edu/grp/scs/net/talk07/aps-apr07.ppt.

Quantitative Measurement of the
Digital Divide
Prepared by: Les CottrellSLAC with Shahryar
KhanNIIT
http://www.slac.stanford.edu/grp/scs/net/talk07/aps-apr07.ppt
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 …
Why Does it Matter
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 dialup 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,
3. Primary health care giver, somewhere in
Acacia Southern
Africa, with sonar machine, digital camera
Africa
and arrangement with national academic
Global Meeting for ICT for
hospital and/or international health institute to UNDP
Development, Ottawa 10-13
assist in diagnostics. After 10 dial-up
July
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
PingER Methodology
Uses ubiquitous ping
Monitoring
host
Internet Remote
Host
(typically
a server)
Data Repository @ SLAC
Measure Round Trip Time & Loss
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/
• >120 countries (99% world’s connected population)
• >35 monitor sites in 14 countries
• Monitor 44 sites in
S. Asia
World Measurements: Min RTT from US
•
•
•
•
Maps show increased coverage
Min RTT indicates best possible, i.e. no queuing
>600ms 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
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
SE Asia
C Asia
Oceania
L America
M East
Africa
Developing
Regions
S Asia
SE Europe
Russia
E Asia
US & Canada
Europe
• Africa, S.
Asia
followed by
M East & L.
America
worst off
Developed
Regions• Africa NOT
improving
Losses
• Mainly distance
independent
• Big impact on
performance,
time outs etc.
• Losses > 2.5 %
have big impact
on interactivity,
VoIP etc.
• N. America, Europe, E. Asia, Oceania < 0.1%
• Underdeveloped 0.3- 2% loss, Africa worst.
• ~ Distance independent
• Calculated as Inter Packet Delay Variation (IPDV)
•
•
•
•
Jitter
– IPDV = Dri = Ri – Ri-1
Measures congestion
Little impact on web, email
Decides length of VoIP codec buffers, impacts streaming Usual
division into
Impacts (with RTT and loss) the quality of VoIP
Developed
vs
Developing
Trendlines for IPDV from SLAC to World Regions
C Asia
Russia
S. Asia
Africa
SE Asia
L. America
M East
Australasia
Europe
N. America
E. Asia
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)
MOS of Various Regions from SLAC
Usable
Improvements
very clear,
often due to
move from
satellite to land
line.
Similar results
from CERN
(less coverage)
World thruput seen from US
Throughput ~
1460Bytes /
(RTT*sqrt(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
Normalized for Details
• Note step
changes
• Africa v.
poor
• S. Asia
improving
• N. America,
Europe, E
Asia,
Oceania
lead
Routing
• Between developing countries often use
transcontinental links (like Europe in 80’s), 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)
Costs compared to West
• Sites in many countries have bandwidth< US residence
– “10 Meg is Here”, www.lightreading.com/document.asp?doc_id=104415
• 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 > average annual income of most Africans,
Survey by Paul Budde Communnications
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
•
•
•
•
•
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.
“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 Forum’s 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)
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
UNDP Human
Development
Index (HDI)
Africa
PingER
- Strong
Correlation
- Non
subjective
- Quicker /
easier to
update
• 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.
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
•
Digital Access infrastructure, affordability, knowledge
and quality and actual usage of ICTs
Index (DAI)
Most European countries > 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
DAI vs. Thru & S. Asia
• More details, also show populations
• Compare S. Asia with developed countries, C. Asia
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
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
More information/Questions
• Acknowledgements:
– Harvey Newman and ICFA/SCIC for a raison d’etre, 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/SubSahara+Case+Study
– https://confluence.slac.stanford.edu/display/IEPM/South+Asia+Ca
se+Study
– http://sdu.ictp.it/lowbandwidth/program/case-studies/index.html