Stanford University, SLAC, NIIT, the Digital Divide & Projects

1. Stanford University, SLAC, NIIT, the Digital Divide & Projects Prepared by Les Cottrell, SLAC for the NIIT Under Graduate Students, March 15, 2007

2. Stanford University • Location

3. Some facts • Founded in 1890’s by Governor Leland Stanford & wife Jane • in memory of son Leland Stanford Jr. • Apocryphal story of foundation • Movies invented at Stanford • 1600 freshman entrants/year (12% acceptance), 7:1 student:faculty, students from 53 countries • 169K living Stanford alumni

4. Some alumni • Sports: Tiger Woods, John McEnroe • Sally Ride Astronaut • Vint Cerf “father of Internet” • Industry: • Hewlett & Packard, Steve Ballmer CEO Microsoft, Scott McNealy Sun … • Ex-presidents: Ehud Barak Israel, Alejandro Toledo Peru • US Politics: Condoleeza Rice, George Schultz, President Hoover

5. Some Startups • Founded Silicon Valley (turned orchards into companies): • Start by providing land and encouragement (investment) for companies started by Stanford alumni, such as HP & Varian • More recently: Sun (Stanford University Network), Cisco, Yahoo, Google

6. Excellence • 17 Nobel prizewinners • Stanford Hospital • Stanford Linear Accelerator Center (SLAC) – my home: • National Lab operated by Stanford University funded by US Department of Energy • Roughly 1400 staff, + contractors & outside users => 3000, ~ 2000 on site at a given time • Fundamental research in: • Experimental particle physics • Theoretical physics • Accelerator research • Astro-physics • Synchrotron Light research • Has faculty to pursue above research and awards degrees, 3 Nobel prizewinners

7. Work with NIIT Start 2004, MoU, funding from Pak MoST & US State Dept. Development of students, build research capacity, develop publicly available tools, publish etc., e.g.: • Quantify the Digital Divide: • Develop a robust measurement infrastructure to provide information on the extent of the Digital Divide • Develop innovative visualization tools • Improve understanding, provide planning information, expectations, identify needs (e.g. last mile problems, fragility, congestion …), report to politicians, funding agencies, net operators, end users, is it good enough for Grids, telemedicine (e.g. consulting expertise for poor communities)… • Case studies for S. Asia, Pakistan, Africa • Provide and deploy tools in Pakistan (NIIT, QAU, PERN) • Geo-location of hosts • Network Weather Forecasting; Anomaly: detection, diagnosis and alerting

8. Students • About a dozen students at NIIT co-supervision SLAC/NIIT • Plus 6 chosen students with internships at SLAC for one year each: • Exposure to National Lab and world class network experts, work on state of the art projects, exposure to high speed networks such as will be available in Pakistan with PERN2, • Take courses at Stanford • 3 currently at SLAC • 3 students completed their year, will return to NIIT as research assistants to share experiences: • One returned to NIIT to pursue PhD • One to startup company in Silicon Valley • One to U of New South Wales

9. Experiences • Extremely successful on-going collaboration • Developed and refined effective ways of communicating at a distance • Useful tool kits developed and made publicly available • Many publications and public presentations • Students hard-working, dedicated, enthusiastic and innovative • Have performed well in course work at Stanford, compare well with Stanford students • Next step: proposal to join the International perfSONAR project (currently: Europe, US & Brazilian NRENs): • provide open set of protocols + ref. implementation for cross-domain sharing of network measurements

10. PingER Project • Arguably the world’s most extensive active end-to-end Internet Performance Project • Digital Divide emphasis • Partially funded by MoST, US State Department • Last three years a joint development effort of SLAC & NIIT • Many NIIT students cut their teeth on it, many papers, presentations • Results: • Highly successful • Identified & quantified rates of improvement for regions/countries • How far behind, catching up, falling behind • Many presentations to funding agencies, politicians, NRENs, recommendations • Case studies identified: fragility of e2e connections, last mile congestion problems, inefficient routing

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

12. Architecture • Monitor hosts send 21 pings each 30 mins to Remote Hosts and cache results • Archive hosts gather data daily, save, analyze & make results available publicly via web

13. PingER Deployment • PingER project originally (1995) to measure 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) • >30 monitor sites in 14 countries • Monitor 44 sites in S. Asia

14. Time Series results • Divides into 2 • India, Maldives, Pakistan, Sri Lanka • Bangladesh, Nepal, Bhutan, Afghanistan • Weekend vs. weekday indicates heavy congestion

15. 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

16. Losses from SLAC to world • # hosts monitored increased seven-fold • Increase in fraction with good loss • Despite adding more hosts in developing world >=12% >=5% <12% >=2.5% < 5% >=1% < 2.5% < 1%

17. 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

18. 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

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

20. Conclusions • Last mile problems, network fragility, poor routing • Decreasing use of satellites, expensive, but still needed for many remote countries in Africa and C. Asia • Africa ~ 10 years behind and falling further behind, leads to “information famine” • Africa big target of opportunity • Growth in # users 2000-2005 200%, Africa 625% • Need more competitive pricing • Fibre competition, government divest for access, low cost VSAT licenses • Consortiums to aggregate & get better pricing ($/BW reduces with BW) • Need better routing - IXPs • Need training & skills for optimal bandwidth management • Internet performance correlates strongly with UNDP & ITU development indices • Increase coverage of monitoring to understand Internet performance

21. Application to PERN • Place PingER monitoring node(s) inside PERN • V. modest host, trivial install • Add traceroute/landmark server for geolocation • PERN configures to monitor to border routers &/or to end hosts at sites (e.g. site web servers) • Currently gathers data daily, analyze, present via SLAC/FNAL • NIIT/SLAC plans to develop front end to analyze/visualize results on real time basis using cached data & RRD/smokeping

22. perfSONAR: Next Generation Network Monitoring • Partnership of Internet2 (US), GEANT (EU), ESnet (US), RNP (Brazil) • Plus in the US: SLAC, U Delaware, GATech • 13 EU related NREN deployments of perfSONAR

23. Needs • Advancements in networks improve scientific collaborations, help accelerate discoveries • E.g. High Energy Physics (HEP), seismology, tele-medicine, astro-physics, global weather, education … • Modern science relies on global Internet • Data exchange, interaction & teleconferencing, Grids … • Network problems have increased significance for science • Thus dependent on cyber infrastructure to support efficient network problem diagnosis along paths traversing multiple network domains • This is an unresolved issue today • Hard to overstate amount of effort today to resolve problems • Often duplicated • Scientists forced to become part-time network engineers

24. Why is this hard? • Internet very diverse, hard to find “invariants, phone models do not work • Constantly changing both short and long-term • Changes are not smooth but usually in steps, findings may be out of date • No central organization • Scientific communities span multiple organizations in many countries • Typical path requires crossing at least 5 administrative domains (campus, regional, backbone, regional and campus) • Domains are autonomous • Measurement not high on vendor’s priorities • ISP’s concerned about privacy, competitive advantage, public embarrassment • Diagnosis hard: • Convince ADs there is a problem and that they could/should help • Need multiple pieces of information from multiple sources (ends, multiple middles…), with no coordinating body • Gets even harder for layer 2 networks

25. New Proposal to Address • Widespread demand for net info by: • Researchers to know how network is performing • Advanced net apps such as Grids (e.g. place data) • Net Ops staffs to diagnose problems • Education • Flexibility in extracting net performance data, needed since • Network changes quickly, diagnostic data is moving target • New tools, metrics and types of analysis are constantly developed • Lack of effective ways to share performance data across domains

26. perfSONAR Infrastructure Provide/Enable Measurement Points and Archives • Provide Authentication/Authorization • Provide registration, discovery & distributed lookup services • Provide open set of protocols + reference implementation for cross-domain sharing of network measurements • Common performance middleware • Open Grid Forum NMWG = extensible XML data representation • All development is open source to encourage widespread development, deployment, ownership & involvement • Early framework prototypes deployed in Europe, N and S America (Brazil), also adopted by LHC

27. Next Steps • Develop scalable, distributed, redundant Federated Lookup Service (like DNS) • Integrate common, existing authentication management into perfSONAR • Design and build the Resource Protector to implement policy • Provide specific, useful example diagnostic services as high quality examples (e.g. for traceroute, ping, one-way delay, SNMP, Layer-2 link services etc.) • Provide a Topology service to provide layer-2 & 3 interconnection information • Promote perfSONAR to research community • Students get reliable data from perfSONAR, request on demand measurements, provide new analyses • Turn into hardened/production quality distributable code

28. Impact NRENs & Customers • R&E relies on reliable networking. • Debugging problems across domains extraordinarily difficult today, increased switched networks will make harder. • PerfSONAR enables divide and conquer between end & intermediate points: • provides easy access to relevant data enables on demand measurements • reduces need to coordinate multi-domain admins (scientist > local net admin > Regional net admin Backbone admin > …), telephone tag, explaining • Reduces participants, hours, days, frustration etc

29. Some Projects

30. One Big Challenge • Elegant graphics are great to understand problems BUT: • Can be thousands of graphs to look at (many site pairs, many devices, many metrics) • Need automated problem recognition AND diagnosis • So developing tools to reliably detect significant, persistent changes in performance • Initially using simple plateau algorithm to detect step changes • Provide reliable alerts • Automatically partially diagnose events • Gather info from routers, monitors etc and eliminate less likely causes

31. Challenges: Finding Hosts • Best via contacts • Also use Google to provide hosts for country (eg .ly) • Found 844 hosts => 702 unique names => 600 ping • 88 unique IP addresses • 6 in Libya according to Geo IP Tool www.geoiptool.com/ • Automated by Akbar Mehdi of NIIT at SLAC (see https://confluence.slac.stanford.edu/display/IEPM/PingER+Host+Searcher ) • Verified with TULIP geolocator • Locates hosts using RTT from multiple landmarks to target • Also see Octant for US www.cs.cornell.edu/~bwong/octant/

32. TULIP geolocator (Faran) • www.slac.stanford.edu/comp/net/wan-mon/tulip/ • Java applet (needs Java Webstart) • Friendly client, easy vizualization • Need landmarks around world Enter target Pings min/avg/max from landmarks to targets Landmarks Target Traceroutes from landmarks to targets

33. Real Time Display of PingER data • Only gather once a day so old • On monitor host, copy data into RRD data base • Use Smokeping or something similar to select & look at data • Important for PERN

34. Case Studies of PingER data • For example we have Sub-Sahara & S. Asia • Need Latin America, Middle-East • How is region doing relative to the world, catching up, falling behind, how far behind? • How are countries doing, RTT, losses, reliability, throughput • How do they compare to development indices • What is routing like

35. Build a Make/Install package for IEPM-BW • We have a new version of our integrated monitoring, archive, analysis, vizualization package • Called Internet End-to-end Monitoring for BandWidth • Hard to install, done twice, once at QAU • Need to make easier and more robust

36. Visualization of IEPM-BW data • Display in real time on a map the connections • Mouse over for information on hosts • Click for performance graphs • Color line by test, • Thickness by performance • Up to you to think about what is available and how to use this to drill down to it…

37. Only a Sample • Lots of work on perfSONAR • Data access via web services • Data registration, discovery lookup • Topology • Event detection • Etc.