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{{NewsItem|2016 May| | {{NewsItem|2016 May| | ||
− | We got the '''best student paper award''' for our work: | + | We got the '''best student paper award''' at the '''MMSYS 2016''' conference for our work: |
<paper authors="G. Cofano, L. De Cicco, T. Zinner, A. Nguyen-Ngoc, P. Tran-Gia, and S. Mascolo" conference="Proc. ACM Mmsys 2016" place="Klagenfurt, Austria" date="May 2016" pdf="network-assistedcontrolcorrected.pdf"> | <paper authors="G. Cofano, L. De Cicco, T. Zinner, A. Nguyen-Ngoc, P. Tran-Gia, and S. Mascolo" conference="Proc. ACM Mmsys 2016" place="Klagenfurt, Austria" date="May 2016" pdf="network-assistedcontrolcorrected.pdf"> |
We got the best student paper award at the MMSYS 2016 conference for our work:
Google Faculty Award 2014 for designing a congestion control algorithm for real-time communication within the WebRTC framework to enable video conference among Web browsers.
Our adaptive video streaming platform is used by:
In this paper we experimentally evaluate the Google Congestion Control (GCC) which has been recently proposed in the RTCWeb IETF WG. By setting up a controlled testbed, we have evaluated to what extent GCC flows are able to track the available bandwidth, while minimizing queuing delays, and fairly share the bottleneck with other GCC or TCP flows. We have found that the algorithm works as expected when a GCC flow accesses the bottleneck in isolation, whereas it is not able to provide a fair bandwidth utilization when a GCC flow shares the bottleneck with either a GCC or a TCP flow.
Cisco Award 2013 Funded by "Cisco University Research Program" managed by the Silicon Valley Community Foundation.This proposal aims at designing a robust, efficient and scalable control system for adaptive (live) video streaming over the best-effort Internet.
Title : Architecture for Robust and Efficient Control of Dynamic Adaptive Video Streaming over HTTP.
In this paper, we present a model of the automatic video stream-switching employed by Akamai along with a description of the client-side communication and control protocol. From the control architecture point of view, the automatic adaptation is achieved by means of two interacting control loops having the controllers at the client and the actuators at the server: one loop is the buffer controller, which aims at steering the client playout buffer to a target length by regulating the server sending rate; the other one implements the stream-switching controller and aims at selecting the video level. A detailed validation of the proposed model has been carried out through experimental measurements in an emulated scenario (IEEE explore link).
We got the best student paper award for our work:
Google Faculty Award 2014 for designing a congestion control algorithm for real-time communication within the WebRTC framework to enable video conference among Web browsers.
Our adaptive video streaming platform is used by:
In this paper we experimentally evaluate the Google Congestion Control (GCC) which has been recently proposed in the RTCWeb IETF WG. By setting up a controlled testbed, we have evaluated to what extent GCC flows are able to track the available bandwidth, while minimizing queuing delays, and fairly share the bottleneck with other GCC or TCP flows. We have found that the algorithm works as expected when a GCC flow accesses the bottleneck in isolation, whereas it is not able to provide a fair bandwidth utilization when a GCC flow shares the bottleneck with either a GCC or a TCP flow.
Cisco Award 2013 Funded by "Cisco University Research Program" managed by the Silicon Valley Community Foundation.This proposal aims at designing a robust, efficient and scalable control system for adaptive (live) video streaming over the best-effort Internet.
Title : Architecture for Robust and Efficient Control of Dynamic Adaptive Video Streaming over HTTP.
In this paper, we present a model of the automatic video stream-switching employed by Akamai along with a description of the client-side communication and control protocol. From the control architecture point of view, the automatic adaptation is achieved by means of two interacting control loops having the controllers at the client and the actuators at the server: one loop is the buffer controller, which aims at steering the client playout buffer to a target length by regulating the server sending rate; the other one implements the stream-switching controller and aims at selecting the video level. A detailed validation of the proposed model has been carried out through experimental measurements in an emulated scenario (IEEE explore link).