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Riga 22: | Riga 22: | ||
A recent focus on bufferbloat has brought a number of new AQM proposals, including '''PIE''' and '''CoDel''', which explicitly control the queuing delay and have no knobs for operators, users or implementers to adjust. This paper considers the '''interplay''' between some of these AQM protocols and the new end-to-end delay-based congestion control algorithm, [http://c3lab.poliba.it/index.php?title=MultimediaCC Google Congestion Control] (GCC) part of the '''WebRTC''' framework. | A recent focus on bufferbloat has brought a number of new AQM proposals, including '''PIE''' and '''CoDel''', which explicitly control the queuing delay and have no knobs for operators, users or implementers to adjust. This paper considers the '''interplay''' between some of these AQM protocols and the new end-to-end delay-based congestion control algorithm, [http://c3lab.poliba.it/index.php?title=MultimediaCC Google Congestion Control] (GCC) part of the '''WebRTC''' framework. | ||
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+ | == Testbed == | ||
+ | [[Immagine:Testbed_aqm.png|1000px|center|''Testbed'']] | ||
+ | <center> '''Testbed Set Up''' </center> | ||
+ | <br> |
Delay sensitive applications require not only congestion control but also minimization of queuing delays to provide interactivity.
This paper considers 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 with delay-based AQM algorithms, namely CoDel and PIE, and flow queuing schedulers, i.e. SFQ and Fq Codel.
For an increasingly important class of Internet applications – such as video conference and personalized live streaming – high delay, rather than limited bandwidth, is the main obstacle to improved performance. A common problem that impacts this class of applications is “bufferbloat”, where excess buffering in the network causes high latency and jitter. Solutions for persistently full buffer problems, active queue management (AQM) schemes such as the original RED, have been known for two decades. Yet, while RED is simple and effective at reducing persistent queues is not widely or consistently configured and enabled in routers and sometimes directly unavailable.
A recent focus on bufferbloat has brought a number of new AQM proposals, including PIE and CoDel, which explicitly control the queuing delay and have no knobs for operators, users or implementers to adjust. This paper considers the interplay between some of these AQM protocols and the new end-to-end delay-based congestion control algorithm, Google Congestion Control (GCC) part of the WebRTC framework.
Delay sensitive applications require not only congestion control but also minimization of queuing delays to provide interactivity.
This paper considers 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 with delay-based AQM algorithms, namely CoDel and PIE, and flow queuing schedulers, i.e. SFQ and Fq Codel.
For an increasingly important class of Internet applications – such as video conference and personalized live streaming – high delay, rather than limited bandwidth, is the main obstacle to improved performance. A common problem that impacts this class of applications is “bufferbloat”, where excess buffering in the network causes high latency and jitter. Solutions for persistently full buffer problems, active queue management (AQM) schemes such as the original RED, have been known for two decades. Yet, while RED is simple and effective at reducing persistent queues is not widely or consistently configured and enabled in routers and sometimes directly unavailable.
A recent focus on bufferbloat has brought a number of new AQM proposals, including PIE and CoDel, which explicitly control the queuing delay and have no knobs for operators, users or implementers to adjust. This paper considers the interplay between some of these AQM protocols and the new end-to-end delay-based congestion control algorithm, Google Congestion Control (GCC) part of the WebRTC framework.