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[[Category:Research]]
 
[[Category:Research]]
=Controlling Queuing Delays for Real-Time Communication:  The Interplay of E2E and AQM Algorithms=
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=Experimental settings for Google Congestion Control for WebRTC=
  
 
Real-time media communication requires not only congestion control, but also minimization of queuing delays to provide interactivity. In this work we consider the case of real-time
 
Real-time media communication requires not only congestion control, but also minimization of queuing delays to provide interactivity. In this work we consider the case of real-time

Revisione 15:39, 30 Mag 2016

Experimental settings for Google Congestion Control for WebRTC

Real-time media communication requires not only congestion control, but also minimization of queuing delays to provide interactivity. In this work we consider the case of real-time communication between web browsers (WebRTC) and we focus on the interplay of an end-to-end delay-based congestion control algorithm, i.e. the Google congestion control (GCC), with two delay-based AQM algorithms, namely CoDel and PIE, and two flow queuing schedulers, i.e. SFQ and Fq_Codel. Experimental investigations show that, when only GCC flows are considered, the end-to-end algorithm is able to contain queuing delays without AQMs. Moreover the interplay of GCC flows with PIE or CoDel leads to higher packet losses with respect to the case of a DropTail queue. In the presence of concurrent TCP traffic, PIE and CoDel reduce the queuing delays with respect to DropTail at the cost of increased packet losses. In this scenario flow queuing schedulers offer a better solution.

Experimental settings and scripts

In order to setup the bottleneck parameters the following scripts can be used:

Experimental settings for Google Congestion Control for WebRTC[edit]

Real-time media communication requires not only congestion control, but also minimization of queuing delays to provide interactivity. In this work we consider the case of real-time communication between web browsers (WebRTC) and we focus on the interplay of an end-to-end delay-based congestion control algorithm, i.e. the Google congestion control (GCC), with two delay-based AQM algorithms, namely CoDel and PIE, and two flow queuing schedulers, i.e. SFQ and Fq_Codel. Experimental investigations show that, when only GCC flows are considered, the end-to-end algorithm is able to contain queuing delays without AQMs. Moreover the interplay of GCC flows with PIE or CoDel leads to higher packet losses with respect to the case of a DropTail queue. In the presence of concurrent TCP traffic, PIE and CoDel reduce the queuing delays with respect to DropTail at the cost of increased packet losses. In this scenario flow queuing schedulers offer a better solution.

Experimental settings and scripts[edit]

In order to setup the bottleneck parameters the following scripts can be used: