CING-YU CHU 2012.08.06 INFOCOM 2012. Outline  Introduction  Measurement  Measurement Results  Modeling Skype Behaviors  Analysis on TCP-friendly.

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Presentation transcript:

CING-YU CHU INFOCOM 2012

Outline  Introduction  Measurement  Measurement Results  Modeling Skype Behaviors  Analysis on TCP-friendly

Motivation  Skype VoIP service is well studied while video service is not  Skype video service consumes more bandwidth Up to 950 kbps  Imperative for network providers and network researchers

Key Questions  Q1: How does a Skype video call adapt its sending rate, video rate and quality under different network conditions?  Q2: Are Skype video calls friendly to TCP flows when they compete for network resources?

Methodology  Measurement Black-box approach Different network setting with ○ configurable packet loss, ○ propagation delay ○ available bandwidth Aim to measure ○ sending rate ○ throughput ○ RTT ○ video bit rate ○ frame rate

Methodology  Modeling Rate control model FEC model Video quality model  Analysis User back-off ○ User-level rate control scheme TCP-friendliness

Contribution  Measures Skype’s stationary behaviors of video calls Sending rate is insensitive to packet loss when PLR < 10% Utilization of the available bandwidth is around 80% Overly aggressive FEC scheme, 4.5 times the PLR

Contribution  Derive various models to verify User back-offs react fast to congestion Skype video calls are TCP-friendly ○ Due to quality-driven user back-offs

Measurement Test-bed

Experiment Design  TV news video sequence “Akiyo” From Joint Video Team (JVT) Head and shoulder movements  Virtual video camera tool  Data collection TCP-dump Skype technical reports

Skype Video Call  On2 video codec Video quantization step Video resolution Number of frames per seconds (FPS)

Measurements Results  Impact of Packet Loss Available Bandwidth Propagation Delay

Impact of Packet Loss  PLR varies from 0% to 12%  Propagation delay: 50ms  3 available bandwidth settings 250 kbps 750 kbps 1000 kbps

Impact of Packet Loss  Forward Error Correction  Two states PLR NORM state PLR >= 10% => CONS state  Different from TCP congestion control scheme

Impact of Available bandwidth  Available Bandwidth varies from 50 kbps to 1000kbps  Two PLRs: 2% and 10%  Propagation delay: 50ms

Impact of Propagation Delay  Propagation delay varies from 50ms to 2000ms  Available bandwidth: 500 kbps  PLR: 0%

Modeling  Sending rate  Video rate  Video Quality

Sending Rate Model  NORM and CONS states  25 scenarios with PLR: 0% to 12% Available bandwidth: 50 kbps to 1000 kbps  γ = 0.77, μ = and δ = 21

Video Rate Model  FEC ratio  FEC ratio model Ψ = 0.15 and ω = 4.5

Video Quality Model  ITU-T Recommendation G.1070 frame rate video rate

Video Quality Model  Frame rate model

Video Quality Model  a = 1.431, b = , c = 3.759, d = 184.1, e = 1.161, h = and g =

Model Validation  Co-current UDP traffic (from iPerf) 0 kbps to 600 kbps  Link capacity: 700 kbps  Propagation delay: 50ms  Available bandwidth for Skype

Model Validation Pearson Correlation Coefficient Sending rateVideo rateFrame rate

Analysis  Q1: How Skype video call users respond to quality degradation resulted from network impairments? How effective user back-offs are as a user-level rate control scheme?  Q2: What is the performance of a Skype video call when it competes with other Skype calls and TCP flows? Is Skype video call TCP-friendly?

Network Model  LTE wireless network Multiple TCP and Skype users M/M/1/K queue using drop-tail Downlink: 100 Mbps, uplink: 50 Mbps

TCP Model  Reacts to packet loss and RTT p = p q + p c t = t q + t c

User-level Rate Control  Video drop-off probability  Number of active users  Effective traffic generated by all users

User-level Rate Control  Average traffic of each user Expected Skype sending rate

Responsiveness to Loss

Responsiveness to Delay

Competition with TCP  p c = 2% and t c = 50ms  N T = # of TCP users, N S = # of Skype users  Aggregate traffic  For each Skype user

Competition with TCP  Scale-up factor: k

Conclusion  Measures Skype video traffic Shows that Skype is robust against mild packet loss and propagation delay Skype can efficiently utilize available bandwidth  Models Skype video behaviors  Shows that Skype video is indeed TCP- friendly Based on user back-off rate control scheme

Q & A