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User-Perceived Performance Measurement on the Internet

User-Perceived Performance Measurement on the Internet. Bill Tice Thomas Hildebrandt CS 6255 November 6, 2003. Introduction. The Internet is different from LANs Diversely administered Users are relatively distant from the network administrators

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User-Perceived Performance Measurement on the Internet

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  1. User-Perceived Performance Measurement on the Internet Bill Tice Thomas Hildebrandt CS 6255 November 6, 2003

  2. Introduction • The Internet is different from LANs • Diversely administered • Users are relatively distant from the network administrators • IP is the only service provided by the network • SNMP or something like it? No…

  3. Overview • Why user-perceived performance measurement is important and also difficult • Existing solutions to the global network measurement problem • NIMI • E2E piPEs • Client-side proxies and other solutions

  4. Performance Measurement on the Internet • IP was designed around the end-to-end argument: certain functions are not required at low levels of a system [1] • As a result, we have a “dumb network” with no built-in performance measurement architecture • The tools we can count on are limited

  5. Performance Measurement on the Internet: Example Tools • Packet Internet Groper (ping) – Useful to test connectivity and RTT between hosts • Traceroute – Provides an approximation of the network topology in the forward direction • Iperf – Measures TCP and UDP performance, including bandwidth, delay jitter and packet loss

  6. Performance Measurement on the Internet • Ping and traceroute rely on ICMP, which is increasingly being blocked by network administrators • Active measurement based on the use of common network services is more robust and perhaps more realistic • DNS queries • HTTP requests

  7. Performance Measurement Architectures • There have been projects to create measurement architectures either by deployment at nodes within domains or at the users • NIMI • E2E pIPEs • AMP, Medusa Proxy, Liston Proxy, Network Weather Service …

  8. NIMI(National Internet Measurement Infrastructure) • Software system for building network measurement infrastructures • Diversely administered • Facilitate many kinds of measurements • Extensible and Modular

  9. NIMI Architecture • Measurement servers (probes) • 2 daemons: nimid and scheduled • Measurement Modules

  10. NIMI Architecture • Configuration Point of Contact (CPOC) • Configuration and Control Servers • Several per domain • Delegation of configuration access

  11. NIMI Architecture • Measurement Client (MC) • Only ‘user’ point of contact with NIMI system • Measurement requests

  12. NIMI Architecture • Data Analysis Client (DAC) • Data Collection • Post-Processing • Run at central location or at MC

  13. NIMI Measurement Modules • NIMI has no knowledge of measurements • Plug-ins • Wrapped for a standard API • Current Modules • traceroute, treno, zing, mflect, traffic, ftp

  14. NIMI Measurements • Request Received from MC • Access Control List • scheduled creates pending measurement • Results sent to DAC by nimid • All communications encrypted

  15. NIMI Deployment • 35 hosts (as of 2001) • Research laboratories and Universities • Georgia Tech • Dead?

  16. NIMI Difficulties • Laboratory Conditions • High bandwidth • Dedicated Resources • Not representative of Internet as a whole

  17. NIMI Difficulties • Meaningful data for User Perceived measurements • Not widely distributed

  18. NIMI Difficulties • Hosts administration difficulties • Tools requiring privileged access • Updates

  19. NIMI Difficulties • Difficult to distribute • What’s in it for me? • Not attractive to average user

  20. E2E piPEs • End-to-end Performance Improvement Performance Environment System • A framework to indicate performance capabilities and locate performance problems along the path between two computers connected by the Abilene network

  21. E2E piPEs Architecture

  22. E2E piPEs Architecture

  23. OWAMP • One-Way Active Measurement Protocol: An Internet2 project • A UDP-based protocol to precisely measure network characteristics: • Loss • Delay • Jitter http://owamp.internet2.edu/ - Under construction

  24. E2E piPEs Status • “The initial deployment, which includes the Abilene backbone network and two campuses only, is scheduled for Fall 2003.” • “piPEfitters” are still developing the system – one suggestion is to place PMPs at the end hosts.

  25. Other Tools: Proxy-Based • Liston Proxy • Between browser and the Web • Handles DNS resolution and content requests • Logs information of interest • DNS responsiveness • Response time

  26. Proxy-Based Tools • Medusa Proxy • Cool name • Monitors performance • DNS • Akamai edge servers vs. origin servers

  27. Proxy-Based Disadvantages • Privacy issues • Overhead • Limited Scope

  28. Distributed Tools • AMP Network • Distributed physical nodes • High Performance Computing (HPC) Network measurement, not user-perceived

  29. Distributed Tools Disadvantages • Wide Distribution • Need large amounts of diverse data • How to do it • Updates • Security

  30. Applications • Network Weather Service • Predicting network performance for applications • Can be run by user to predict their performance

  31. Applications • Lots • Zing • Ping • IPerf • Traceroute

  32. NM Applications Disadvantages • Limited Scope • Generally Stateless

  33. User-Perceived Performance Measurement: Why? • Because the Internet was designed following the end-to-end principle, end-to-end performance is ultimately the most meaningful to measure • It is difficult to deploy a measurement architecture in the Internet backbone • Network users see end-to-end performance directly and could be effectively used as monitor points

  34. User-Perceived Measurement: How? • The infrastructure • NIMI-like plug-in measurement modules • Standardized communication between components

  35. User-Perceived Measurement: How? • Distribution • Have to make it something users want to run

  36. User-Perceived Measurement: How? • Processing • Centralized data collection and post-processing

  37. References • [1] J.H. Saltzer, D.P. Reed, and D.D. Clark. “End to End Arguments in System Design.” http://web.mit.edu/Saltzer/www/publications/endtoend/endtoend.txt • [2] Vern Paxson, Andrew Adams, and Matt Mathis. “Experiences with NIMI.” In Proceedings of Passive and Active Measurement, 2000. http://citeseer.nj.nec.com/paxson00experiences.html • [3] Internet2. E2E piPEs. http://e2epi.internet2.edu/E2EpiPEs/e2epipe_index.html • [4] Richard Liston and Ellen Zegura. “Using a Proxy to Measure Client-Side Web Performance.” Proceedings of the 6th International Web Caching and Content Distribution Workshop, Boston, MA, June 1999. http://www.cc.gatech.edu/~liston/pubs/proxy_wcw01.ps.gz • Network Weather Service http://www.npaci.edu/envision/v15.2/nws.html

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