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User-Perceived Performance Measurement on the Internet: Challenges and Solutions

This document explores the complexities of measuring user-perceived performance on the Internet, in contrast to Local Area Networks (LANs). With users distanced from network administrators, measuring performance becomes challenging due to the lack of built-in measurement tools in Internet Protocol (IP). Key approaches discussed include the National Internet Measurement Infrastructure (NIMI), end-to-end performance improvement methods like E2E.piPEs, and various performance measurement tools, such as ping, traceroute, and proxy-based solutions. Their impact on real-world Internet performance assessment is critically analyzed.

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User-Perceived Performance Measurement on the Internet: Challenges and Solutions

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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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