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Network reliability and QoS measurements

Explore service availability metrics for VoIP, evaluating call success probability, network loss, outages, and call interruption rates for improved quality and reliability. Research assesses Voice over Internet Protocol using Columbia University's IRT Lab data from March 2003.

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Network reliability and QoS measurements

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  1. Network reliability and QoS measurements Henning Schulzrinne University of Cincinnati March 2003

  2. Overview • The IRT Lab at Columbia University • Application: Internet multimedia • Quality of service = • scheduling and admission control  thousands of papers… • network signaling • end-system performance  embedded end systems + PCs • QoS  network application reliability

  3. Laboratory overview • 11 PhDs • 3 at IBM, Lucent, Telcordia • 5 MS • Visitors (Ericsson, Fujitsu, Mitsubishi, Nokia, U. Coimbra, U. Oulu, …) • China, Finland, Greece, India, Japan, Portugal, Spain, Sweden, US, Taiwan

  4. IRT topics • Internet multimedia protocols and systems • Internet telephony and radio (SIP, RTSP, RTP) • Content distribution networks • Internet-scale event distribution • Service creation • Ubiquitous, context-aware computing and communications • Protocols and services for wireless ad-hoc networks • Service discovery • Quality of service • Pricing for adaptive services • Scalable resource reservation protocols (CASP, BGRP, YESSIR) • End-system evaluation • Network measurements • Service reliability

  5. Internet multimedia • Internet telephony = replacing the existing circuit-switched system with Internet-based systems • Signaling and services • Quality of service philosophies: • end systems adapt and compensate • end systems use FEC, LBR, PLC • jitter  playout delay compensation • network offers guarantees  difficult architecturally, business, not necessarily technically • we pursue both

  6. Assessment of VoIP Service Availability Wenyu Jiang Henning Schulzrinne IRT Lab, Dept. of Computer Science Columbia University

  7. Overview (on-going work, preliminary results, still looking for measurement sites, …) • Service availability • Measurement setup • Measurement results • call success probability • overall network loss • network outages • outage induced call abortion probability

  8. Service availability • Users do not care about QoS • at least not about packet loss, jitter, delay • FEC and PLC can deal with losses up to 5-8% • rather, it’s service availability how likely is it that I can place a call and not get interrupted? • availability = MTBF / (MTBF + MTTR) • MTBF = mean time between failures • MTTR = mean time to repair • availability = successful calls / first call attempts • equipment availability: 99.999% (“5 nines”)  5 minutes/year • AT&T: 99.98% availability (1997) • IP frame relay SLA: 99.9% • UK mobile phone survey: 97.1-98.8%

  9. Availability – PSTN metrics • PSTN metrics (Worldbank study): • fault rate • “should be less than 0.2 per main line” • fault clearance (~ MTTR) • “next business day” • call completion rate • during network busy hour • “varies from about 60% - 75%” • dial tone delay

  10. Example PSTN statistics Source: Worldbank

  11. Measurement setup

  12. Measurement setup • Active measurements • call duration 3 or 7 minutes • UDP packets: • 36 bytes alternating with 72 bytes (FEC) • 40 ms spacing • September 10 to December 6, 2002 • 13,500 call hours

  13. Call success probability • 62,027 calls succeeded, 292 failed  99.53% availability • roughly constant across I2, I2+, commercial ISPs

  14. Overall network loss • PSTN: once connected, call usually of good quality • exception: mobile phones • compute periods of time below loss threshold • 5% causes degradation for many codecs • others acceptable till 20%

  15. Network Outages • sustained packet losses • arbitrarily defined at 8 packets • far beyond any recoverable loss (FEC, interpolation) • 23% outages • make up significant part of 0.25% unavailability • symmetric: AB  BA • spatially correlated: AB   AX • not correlated across networks (e.g., I2 and commercial)

  16. Network outages

  17. Network outages

  18. Outage-induced call abortion proability • Long interruption  user likely to abandon call • from E.855 survey: P[holding] = e-t/17.26 (t in seconds) •  half the users will abandon call after 12s • 2,566 have at least one outage • 946 of 2,566 expected to be dropped  1.53% of all calls

  19. Conclusion • Availability in space is (mostly) solved  availability in time restricts usability for new applications • initial investigation into service availability for VoIP • need to define metrics for, say, web access • unify packet loss and “no Internet dial tone’’ • far less than “5 nines” • working on identifying fault sources and locations • looking for additional measurement sites

  20. Quality and Performance Evaluation of VoIP End-points Wenyu Jiang Henning Schulzrinne Columbia University

  21. Motivations • The quality of VoIP depends on both the network and the end-points • Extensive QoS literature on network performance, e.g., IntServ, DiffServ • Focus is on limiting network loss & delay • Little is known about the behavior of VoIP end-points

  22. Performance Metrics for VoIP End-points • Mouth-to-ear (M2E) delay • compare network delay • Clock skew • whether it causes any voice glitches • amount of clock drift • Silence suppression behavior • whether the voice is clipped (depends much on hangover time) • robustness to non-speech input, e.g., music • Robustness to packet loss • voice quality under packet loss • Acoustic echo cancellation • Jitter adaptation: delay > max(jitter)?

  23. Measurement Approach • Capture both original and output audio • Use adelay program to measure M2E delay • auto correlation • no clock synchronization needed • Assume a LAN environment by default • Serve as a baseline of reference, or lower bound

  24. VoIP End-points Tested • Hardware End-points • Cisco, 3Com and Pingtel IP phones • Mediatrix 1-line SIP/PSTN Gateway • Software clients • Microsoft Messenger, NetMeeting (Win2K, WinXP) • Net2Phone (NT, Win2K, Win98) • Sipc/RAT (Solaris, Ultra-10) • Robust Audio Tool (RAT) from UCL as media client • Operating parameters: • In most cases, codec is G.711 -law, packet interval is 20ms

  25. IP Phone Hardware • DSP for audio coding, AEC • C for protocol processing • embedded OS (Linux, Windriver, …) with web browser • Ethernet interface, maybe with hub

  26. Example M2E Delay Plot • 3Com to Cisco, shown with gaps > 1sec • Delay adjustments correlate with gaps, despite 3Com phone has no silence suppression

  27. Visual Illustration of M2E Delay Drop, Snapshot #1 • 3Com to Cisco 1-1 case • Left/upper channel is original audio • Highlighted section shows M2E delay (59ms)

  28. Snapshot #2 • M2E delay drops to 49ms, at time of 4:16

  29. Snapshot #3 • Presence of a gap during the delay change

  30. Effect of RTP Marker Bits on Delay Adjustments • Cisco phone sends M-bits, whereas Pingtel phone does not • Presence of M-bits results in more adjustments

  31. Sender Characteristics • Certain senders may introduce delay spikes, despite operating on a LAN

  32. Average M2E Delays for IP phones and sipc • Averaging the M2E delay allows more compact presentation of end-point behaviors • Receiver (especially RAT) plays an important role in M2E delay

  33. Average M2E Delays for PC Software Clients • Messenger 2000 wins the day • Its delay as receiver (68ms) is even lower than Messenger XP, on the same hardware • It also results in slightly lower delay as sender • NetMeeting is a lot worse (> 400ms) • Messenger’s delay performance is similar to or better than a GSM mobile phone.

  34. Delay Behaviors for PC Clients, contd. • Net2Phone’s delay is also high • ~200-500ms • V1.5 reduces PC->PSTN delay • PC-to-PC calls have fairly high delays

  35. Effect of Clock Skew: Cisco to 3Com, Experiment 1-1 • Symptom of playout buffer underflow • Waveforms are dropped • Occurred at point of delay adjustment • Bugs in software?

  36. Clock Skew Rates • Mostly symmetric between two devices • RAT (Sun Ultra-10) has unusually high drift rates, > 300 ppm (parts per million) • High clock skews confirmed in many (but not all) PCs and workstations

  37. Drift Rates for PC Clients • Drift Rates not always symmetric! • But appears to be consistent between Messenger 2K/XP and Net2Phone on the same PC • Existence of 2 clocking circuits in sound card?

  38. Packet Loss Concealment • Common PLC methods • Silence substitution (worst) • Packet repetition, with optional fading • Extrapolation (one-sided) • Interpolation (two-sided), best quality • Use deterministic bursty loss pattern • 3/100 means 3 consecutive losses out of every 100 packets • Easier to locate packet losses • Tested 1/100, 3/100, 1/20, 5/100, etc.

  39. PLC Behaviors • Loss tolerance (at 20ms interval) • By measuring loss-induced gaps in output audio • 3Com and Pingtel phones: 2 packet losses • Cisco phone: 3 packet losses • Level of audio distortion by packet loss • Inaudible at 1/100 for all 3 phones • Inaudible at 3/100 and 1/20 for Cisco phone, yet audible to very audible for the other two. • Cisco phone is the most robust • Probably uses interpolation

  40. Effect of PLC on Delay • No affirmative effect on M2E delay • E.g., sipc to Pingtel

  41. Silence Suppression • Why? • Saves bandwidth • May reduce processing power (e.g., in conferencing mixer) • Facilitates per-talkspurt delay adjustment • Key parameters • Silence detection threshold • Hangover time, to delay silence suppression and avoid end clipping of speech • Usually 200ms is long enough [Brady ’68]

  42. Hangover Time • Measured by feeding ON-OFF waveforms and monitor RTP packets • Cisco phone’s is the longest (2.3-2.36 sec), then Messenger (1.06-1.08 sec), then NetMeeting (0.56-0.58 sec) • A long hangover time is not necessarily bad, as it reduces voice clipping • Indeed, no unnatural gaps are found • Does waste a bit more bandwidth

  43. Robustness of Silence Detectors to Music • On-hold music is often used in customer support centers • Need to ensure music is played without any interruption due to silence suppression • Tested with a 2.5-min long soundtrack • Messenger starts to generate many unwanted gaps at input level of -24dB • Cisco phone is more robust, but still fails from input level of -41.4dB

  44. Acoustic Echo Cancellation • Important for hands-free/conferencing (business) applications • Primary metric: Echo Return Loss (ERL) • Measured by LAN-sniffing RTP packets • Most IP phones support AEC • ERL depends slightly on input level and speaker-phone volume • Usually > 40 dB (good AEC performance)

  45. M2E Delay under Jitter • Delay properties under the LAN environment serves as a baseline of reference • When operating over the Internet: • Fixed portion of delay adds to M2E delay as a constant • Variable portion (jitter) has a more complex effect • Initial test • Used typical cable modem delay traces • Tested RAT to Cisco • No audible distortion due to late loss • Added delay is normal

  46. M2E Delay under Jitter, contd. • Cisco phone generally within expectation • Can follow network delay change timely • Takes longer (10-20sec) to adapt to decreasing delay • Does not overshoot playout delay • More end-points to be examined Artificial Trace Real Trace with Spikes

  47. Conclusions • Average M2E Adelay: • Low (mostly < 80ms) for hardware IP phones • Software clients: lowest for Messenger 2000 (68.5ms) • Application (receiver) most vital in determining delay • Poor implementation easily undoes good network QoS • Clock skew high on SW clients (RAT, Net2Phone) • Packet loss concealment quality • Acceptable in all 3 IP phones tested, w. Cisco more robust • Silence detector behavior • Long hangover time, works well for speech input • But may falsely predict music as silence • Acoustic Echo Cancellation: good on most IP phones • Playout delay behavior: good based on initial tests

  48. Future Work • Further tests with more end-points on how jitter influences M2E delay • Measure the sensitivity (threshold) of various silence detectors • Investigate the non-symmetric clock drift phenomena • Additional experiments as more brands of VoIP end-points become available

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