Congestion Control for Multimedia Applications

The congestion control for multimedia applications (Voice over IP, video on demand) is an open issue. We have evaluated the congestion control strategies employed by leading multimedia applications such as Skype for VoIP applications and RealNetworks video on demand applications. We have found that both applications don't employ an efficient congestion control scheme.

Multimedia application

Skype Video Responsiveness to Bandwidth Variations

Nowadays, the Internet is rapidly evolving to become an equally efficient platform for multimedia content delivery. Key examples are YouTube, Skype Audio/Video, IPTV, P2P video distribution platforms such as Coolstreaming or Joost, to name few. While YouTube streams videos using the Transmission Control Protocol (TCP), applications that are time-sensitive such as Skype VoIP or Video Conferencing employ the UDP because they can tolerate small loss percentages but not delays due to TCP recovery of losses via retransmissions. Since the UDP does not implement congestion control, these applications must implement those functionalities at the application layer. This paper investigates Skype Video in order to discover at what extent this application is able to throttle its sending rate to match the unpredictable Internet bandwidth while preserving resource for co-existing best-effort TCP traffic.

  • L. De Cicco, S. Mascolo, V. Palmisano
    Skype Video Responsiveness to Bandwidth Variations
    ACM NOSSDAV '08, Braunschweig, Germany, May, 2008 (PDF)

Skype VoIP Congestion Control

Skype is the most popular VoIP application with over 250 million userbase spread all over the world. It is important to study how skype reacts to packet losses in order to infer if a huge amount of skype calls can result in a congestion collapse.

Next figures summarize main findings (more can be found in the paper: "An Experimental Investigation of the Congestion Control Used by Skype VoIP" pdf and slides).

Skype implements some mechanism to adapt the input rate to the available bandwidth

One Skype flow over a square waveform available bandwidth

The figure shows the sending rate, the loss rate and the available bandwidth. It can be noticed that Skype adapts its sending rate when the available bandwidth decreases but this adaptation takes 40s, thus leading to high packet loss rates.

Skype adapts to the available bandwidth very slowly

For the before mentioned reason Skype is not able to cope with sudden bandwidth variations as it can be seen in the next figure.

One Skype flow over a square waveform available bandwidth (higher frequency than before)


Skype is not TCP friendly

Skype's response to bandwidth variation is sluggish and leads to unfriendliness with respect to TCP flows.

One Skype flow versus one TCP flow

The Figure above shows that TCP connection suffers a large number of timeouts.

Skype is not able to guarantee fairness either

Two Skype calls have been placed flowing in the same bottleneck in order to investigate if Skype's congestion control is able to guarantee fairness.

Two Skype flows sharing the same bottleneck

Apple Darwin Streaming Server Congestion Control

We investigated the end-to-end quality of service (QoS) that is provided by the Apple Darwin Streaming Server and the Quick-Time client player in the presence of time-varying available bandwidth and multiple concurrent streaming sessions.

More can be found in the paper: An Experimental Investigation of the End-to-End QoS of the Apple Darwin Streaming Server (pdf).

Helix Player Congestion Control (RealPlayer by RealNetworks)

We have evaluated how Helix Player behaves when available bandwidth reductions take place in order to find out how it reacts to congestion episodes. The figure below shows how the throughput of an helix connection experiences up to 30% of packet losses when another helix flow enters the link at 30s and exits at 90s.

Two Helix flows sharing a bottleneck

Relevant bibliography

  • L. De Cicco, S. Mascolo, V. Palmisano
    A Mathematical Model of the Skype VoIP Congestion Control Algorithm
    to appear in IEEE Conference on Decision and Control 2008, Cancun, Mexico, Dec, 2008 (PDF)
  • L. De Cicco, S. Mascolo, V. Palmisano
    Skype Video Responsiveness to Bandwidth Variations
    NOSSDAV '08, Braunschweig, Germany, May, 2008 (PDF) (Slides:PDF)
  • L. De Cicco, S. Mascolo, V. Palmisano
    An Experimental Investigation of the End-to-End QoS of the Apple Darwin Streaming Server
    Wired/Wireless Internet Communications (WWIC) 2008, May, 2008 (PDF)
  • L. De Cicco, S. Mascolo and V. Palmisano
    An Experimental Investigation of the Congestion Control Used by Skype VoIP
    Wired/Wireless Internet Communications (WWIC) 2007, Coimbra, Portugal, May, 2007 (PDF) (Slides:PDF)
  • L.A. Grieco, S. Mascolo,
    Adaptive Rate Control for Streaming Flows over the Internet
    ACM Multimedia Systems Journal, Regular paper, Volume 9, Issue 6, pp. 517 - 532, Jun. 2004



This page is mantained by Luca De Cicco, please send feedback to ldecicco at gmail DOT com

Congestion Control for Multimedia Applications[edit]

The congestion control for multimedia applications (Voice over IP, video on demand) is an open issue. We have evaluated the congestion control strategies employed by leading multimedia applications such as Skype for VoIP applications and RealNetworks video on demand applications. We have found that both applications don't employ an efficient congestion control scheme.

Multimedia application

Skype Video Responsiveness to Bandwidth Variations[edit]

Nowadays, the Internet is rapidly evolving to become an equally efficient platform for multimedia content delivery. Key examples are YouTube, Skype Audio/Video, IPTV, P2P video distribution platforms such as Coolstreaming or Joost, to name few. While YouTube streams videos using the Transmission Control Protocol (TCP), applications that are time-sensitive such as Skype VoIP or Video Conferencing employ the UDP because they can tolerate small loss percentages but not delays due to TCP recovery of losses via retransmissions. Since the UDP does not implement congestion control, these applications must implement those functionalities at the application layer. This paper investigates Skype Video in order to discover at what extent this application is able to throttle its sending rate to match the unpredictable Internet bandwidth while preserving resource for co-existing best-effort TCP traffic.

Skype VoIP Congestion Control[edit]

Skype is the most popular VoIP application with over 250 million userbase spread all over the world. It is important to study how skype reacts to packet losses in order to infer if a huge amount of skype calls can result in a congestion collapse.

Next figures summarize main findings (more can be found in the paper: "An Experimental Investigation of the Congestion Control Used by Skype VoIP" pdf and slides).

Skype implements some mechanism to adapt the input rate to the available bandwidth[edit]

One Skype flow over a square waveform available bandwidth

The figure shows the sending rate, the loss rate and the available bandwidth. It can be noticed that Skype adapts its sending rate when the available bandwidth decreases but this adaptation takes 40s, thus leading to high packet loss rates.

Skype adapts to the available bandwidth very slowly[edit]

For the before mentioned reason Skype is not able to cope with sudden bandwidth variations as it can be seen in the next figure.

One Skype flow over a square waveform available bandwidth (higher frequency than before)


Skype is not TCP friendly[edit]

Skype's response to bandwidth variation is sluggish and leads to unfriendliness with respect to TCP flows.

One Skype flow versus one TCP flow

The Figure above shows that TCP connection suffers a large number of timeouts.

Skype is not able to guarantee fairness either[edit]

Two Skype calls have been placed flowing in the same bottleneck in order to investigate if Skype's congestion control is able to guarantee fairness.

Two Skype flows sharing the same bottleneck

Apple Darwin Streaming Server Congestion Control[edit]

We investigated the end-to-end quality of service (QoS) that is provided by the Apple Darwin Streaming Server and the Quick-Time client player in the presence of time-varying available bandwidth and multiple concurrent streaming sessions.

More can be found in the paper: An Experimental Investigation of the End-to-End QoS of the Apple Darwin Streaming Server (pdf).

Helix Player Congestion Control (RealPlayer by RealNetworks)[edit]

We have evaluated how Helix Player behaves when available bandwidth reductions take place in order to find out how it reacts to congestion episodes. The figure below shows how the throughput of an helix connection experiences up to 30% of packet losses when another helix flow enters the link at 30s and exits at 90s.

Two Helix flows sharing a bottleneck

Relevant bibliography[edit]



This page is mantained by Luca De Cicco, please send feedback to ldecicco at gmail DOT com