(Congestion Control for Multimedia Applications)
(Congestion Control for Multimedia Applications)
Riga 4: Riga 4:
 
[[Immagine:Multimedia-cc.png|right|thumb|400px|''Multimedia application'']]
 
[[Immagine:Multimedia-cc.png|right|thumb|400px|''Multimedia application'']]
  
=='''Helix Player Congestion Control''' (RealNet)==
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=='''Helix Player Congestion Control''' (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.  
 
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.  
 
[[Immagine:helix-cc.png|right|thumb|400px|''Two Helix flows sharing a bottleneck'']]
 
[[Immagine:helix-cc.png|right|thumb|400px|''Two Helix flows sharing a bottleneck'']]

Revisione 11:00, 15 Dic 2006

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 out that both applications doesn't employ an efficient congestion control scheme.

Multimedia application

Helix Player Congestion Control (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

Skype 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.

Towards this end we have evaluated Skype generated flows in a local testbed. We have routed the traffic of two Skype users hosted on the same machine through a virtual machine where "tc" and "netem" have been configured in order to add delays and and to control link capacity (see figure below).

Testbed employed to test Skype

The figure below shows how Skype behaves when the link suffers drops in capacity. We have set up the link capacity to vary between 20 Kbyte/s and 2 Kbyte/s as a square wave with 50% duty cycle and 30s period. The figure clearly shows (see the loss percentage) that Skype is not able to react to link capacity drops leading to very high packet loss rates (up to 80%) when the link capacity is reduced.

Skype connection

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 out that both applications doesn't employ an efficient congestion control scheme.

Multimedia application

Helix Player Congestion Control (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

Skype 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.

Towards this end we have evaluated Skype generated flows in a local testbed. We have routed the traffic of two Skype users hosted on the same machine through a virtual machine where "tc" and "netem" have been configured in order to add delays and and to control link capacity (see figure below).

Testbed employed to test Skype

The figure below shows how Skype behaves when the link suffers drops in capacity. We have set up the link capacity to vary between 20 Kbyte/s and 2 Kbyte/s as a square wave with 50% duty cycle and 30s period. The figure clearly shows (see the loss percentage) that Skype is not able to react to link capacity drops leading to very high packet loss rates (up to 80%) when the link capacity is reduced.

Skype connection