International audienceNowadays, video data transfers account for much of the Internet traffic and a huge number of users use this service on a daily base. Even if videos are usually stored in several bitrates on servers, the video sending rate does not take into account network conditions which are changing dynamically during transmission. Therefore, the best bitrate is not used which causes sub-optimal video quality when the video bitrate is under the available bandwidth or packet loss when it is over it. One solution is to deploy adaptive video, which adapts video parameters such as bitrate or frame resolution to network conditions. Many ideas are proposed in the literature, yet no paper provides a global view on adaptation methods in order to classify them. This article fills this gap by discussing several adaptation methods through a taxonomy of the parameters used for adaptation. We show that, in the research community, the sender generally takes the decision of adaptation whereas in the solutions supported by major current companies the receiver takes this decision. We notably suggest, without evaluation, a valuable and realistic adaptation method, gathering the advantages of the presented methods

Nowadays, video data transfers account for much of the Internet bandwidth and a huge number of users use it daily. However, despite its apparent interest, video streaming is still done in a suboptimal manner. Indeed, more and more high definition and high quality videos are nowadays stored on Internet but they are not accessible for everybody because a high and stable bandwidth is needed to stream them; also, during video conferencing, the highest possible quality often exceeds the available bandwidth. Hence, a lower bitrate encoding is usually chosen but it leads to lower quality and network under-utilisation too. This paper presents VAAL, a simple and efficient method designed to use optimally network resources and to ameliorate user video experience. It involves only the application layer on the server. The main idea of VAAL is that it checks TCP-friendly transport protocol buffer overflows and adapts the video bitrate accordingly; as a result, the bitrate constantly matches the network bandwidth. It can be used together with ZAAL, a novel algorithm aiming to avoid quality oscillations. Experimental results show that the video adaptation using VAAL+ZAAL performs much better compared to the currently widely-used static encoding, making it a strong candidate for hard real-time video streaming.

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International audienceOne major yet unsolved problem in wired-cum-wireless networks is the classification of losses, which might result from wireless temporary interferences or from network congestion. The transport protocol response to losses should be different for these two cases. If the transmission uses existing protocols like TCP, the losses are always classified as congestion losses by sender, causing reduced throughput. In wired networks, ECN (Explicit Congestion Notification) can be used to control the congestion through active queue management such as RED (Random Early Detection). It can also be used to solve the transport protocol misreaction over wireless networks. This paper proposes a loss differentiation method (RELD), based on ECN signaling and RTT, and applied to TCPlike. TCPlike is one of the three current congestion controls present in the new transport protocol DCCP (Datagram Congestion Control Protocol). Our simulations, using a more realistic simulated loss error model for wireless networks, show that RELD optimizes congestion control and therefore increases the performance of transport protocols over wireless networks, leading to an average performance gain ranging from 10% to 15%

One major yet unsolved problem in wired-cumwireless networks is the classification of losses, which can be due either to wireless temporary interferences or to network congestion. The transport protocol response to losses has to be different for these two cases. If the transmission uses existing protocols like TCP, the losses will always be classified as congestion losses by the data sender, causing reduced throughput. In wired networks, ECN (Explicit Congestion Notification) can be used to control the congestion through active queue management such as RED (Random Early Detection). It can also be used to resolve the transport protocol misreaction on wireless networks. This paper proposes a loss differentiation method (EcnLD), based on ECN signaling and RTT, and applied to TCPlike. TCPlike is one of the two current congestion controls present in the new transport protocol DCCP (Datagram Congestion Control Protocol). Our results indicate that EcnLD is a good approach to optimize congestion control and therefore increase the performance of transport protocols over wireless networks.