Oscillation-free video adaptation at application layer on server side and experiments using DCCP

International audienceNowadays, 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 videoconferencing, 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-utilization too. This paper presents Video Adaptation at Application Layer (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 Transmission Control Protocol-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 Zigzag Avoidance Algorithm (ZAAL), a novel algorithm aiming to avoid quality oscillations. Experimental results show that the video adaptation using VAAL+ZAAL performs much better compared with the currently widely used static encoding, making it a strong candidate for hard real-time video streaming

A taxonomy of the parameters used by decision methods for adaptive video transmission

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

Quality-Oriented Mobility Management for Multimedia Content Delivery to Mobile Users

The heterogeneous wireless networking environment determined by the latest developments in wireless access technologies promises a high level of communication resources for mobile computational devices. Although the communication resources provided, especially referring to bandwidth, enable multimedia streaming to mobile users, maintaining a high user perceived quality is still a challenging task. The main factors which affect quality in multimedia streaming over wireless networks are mainly the error-prone nature of the wireless channels and the user mobility. These factors determine a high level of dynamics of wireless communication resources, namely variations in throughput and packet loss as well as network availability and delays in delivering the data packets. Under these conditions maintaining a high level of quality, as perceived by the user, requires a quality oriented mobility management scheme. Consequently we propose the Smooth Adaptive Soft-Handover Algorithm, a novel quality oriented handover management scheme which unlike other similar solutions, smoothly transfer the data traffic from one network to another using multiple simultaneous connections. To estimate the capacity of each connection the novel Quality of Multimedia Streaming (QMS) metric is proposed. The QMS metric aims at offering maximum flexibility and efficiency allowing the applications to fine tune the behavior of the handover algorithm. The current simulation-based performance evaluation clearly shows the better performance of the proposed Smooth Adaptive Soft-Handover Algorithm as compared with other handover solutions. The evaluation was performed in various scenarios including multiple mobile hosts performing handover simultaneously, wireless networks with variable overlapping areas, and various network congestion levels

Congestion control for cloud gaming over udp based on round-Trip video latency

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksWe describe a network congestion control mechanism for cloud gaming (CG) platforms based on the user datagram protocol (UDP). To minimize the contribution of the downstream transmission delay to the total end-To-end latency in the interaction-perception loop, we first define the round-Trip video latency (RTVL) and develop a congestion model. Based on them, we design and implement an adaptation strategy that detects the early stages of congestion to prevent high values of RTVL and network bufferbloat, thus avoiding packet losses. Using data measured from the network, our strategy modifies the target output bitrate of the video encoder to throttle down or upto the data flow sent by the server to the client. In the presence of sudden downstream channel capacity drops of over 40%, our algorithm reactively manages to satisfy the key CG requirements for interactive games by entirely avoiding the packet losses and keeping the RTVL below 100 ms. In reasonably stable network conditions, our algorithm proactively keeps exploring for higher bitrates and building a 'network state dictionary,' due to which it achieves an effective downstream channel capacity use of 95%This work was supported in part by the Ministerio de Ciencia, Innovación y Universidades (AEI/FEDER) of the Spanish Government through the Project ‘‘Open Graphics Gaming Cloud’’ under Grant RTC-2016-5676-7 and the Project ‘‘Immersive Visual Media Environments’’ under Grant TEC2016-7598

Dual-Mode Congestion Control Mechanism for Video Services

Recent studies have shown that video services represent over half of Internet traffic, with a growing trend. Therefore, video traffic plays a major role in network congestion. Currently on the Internet, congestion control is mainly implemented through overprovisioning and TCP congestion control. Although some video services use TCP to implement their transport services in a manner that actually works, TCP is not an ideal protocol for use by all video applications. For example, UDP is often considered to be more suitable for use by real-time video applications. Unfortunately, UDP does not implement congestion control. Therefore, these UDP-based video services operate without any kind of congestion control support unless congestion control is implemented on the application layer. There are also arguments against massive overprovisioning. Due to these factors, there is still a need to equip video services with proper congestion control.Most of the congestion control mechanisms developed for the use of video services can only offer either low priority or TCP-friendly real-time services. There is no single congestion control mechanism currently that is suitable and can be widely used for all kinds of video services. This thesis provides a study in which a new dual-mode congestion control mechanism is proposed. This mechanism can offer congestion control services for both service types. The mechanism includes two modes, a backward-loading mode and a real-time mode. The backward-loading mode works like a low-priority service where the bandwidth is given away to other connections once the load level of a network is high enough. In contrast, the real-time mode always demands its fair share of the bandwidth.The behavior of the new mechanism and its friendliness toward itself, and the TCP protocol, have been investigated by means of simulations and real network tests. It was found that this kind of congestion control approach could be suitable for video services. The new mechanism worked acceptably. In particular, the mechanism behaved toward itself in a very friendly way in most cases. The averaged TCP fairness was at a good level. In the worst cases, the faster connections received about 1.6 times as much bandwidth as the slower connections

Congestion Control for Streaming Media

The Internet has assumed the role of the underlying communication network for applications such as file transfer, electronic mail, Web browsing and multimedia streaming. Multimedia streaming, in particular, is growing with the growth in power and connectivity of today\u27s computers. These Internet applications have a variety of network service requirements and traffic characteristics, which presents new challenges to the single best-effort service of today\u27s Internet. TCP, the de facto Internet transport protocol, has been successful in satisfying the needs of traditional Internet applications, but fails to satisfy the increasingly popular delay sensitive multimedia applications. Streaming applications often use UDP without a proper congestion avoidance mechanisms, threatening the well-being of the Internet. This dissertation presents an IP router traffic management mechanism, referred to as Crimson, that can be seamlessly deployed in the current Internet to protect well-behaving traffic from misbehaving traffic and support Quality of Service (QoS) requirements of delay sensitive multimedia applications as well as traditional Internet applications. In addition, as a means to enhance Internet support for multimedia streaming, this dissertation report presents design and evaluation of a TCP-Friendly and streaming-friendly transport protocol called the Multimedia Transport Protocol (MTP). Through a simulation study this report shows the Crimson network efficiently handles network congestion and minimizes queuing delay while providing affordable fairness protection from misbehaving flows over a wide range of traffic conditions. In addition, our results show that MTP offers streaming performance comparable to that provided by UDP, while doing so under a TCP-Friendly rate

Protocols and Algorithms for Adaptive Multimedia Systems

The deployment of WebRTC and telepresence systems is going to start a wide-scale adoption of high quality real-time communication. Delivering high quality video usually corresponds to an increase in required network capacity and also requires an assurance of network stability. A real-time multimedia application that uses the Real-time Transport Protocol (RTP) over UDP needs to implement congestion control since UDP does not implement any such mechanism. This thesis is about enabling congestion control for real-time communication, and deploying it on the public Internet containing a mixture of wired and wireless links. A congestion control algorithm relies on congestion cues, such as RTT and loss. Hence, in this thesis, we first propose a framework for classifying congestion cues. We classify the congestion cues as a combination of: where they are measured or observed? And, how is the sending endpoint notified? For each there are two options, i.e., the cues are either observed and reported by an in-path or by an off-path source, and, the cue is either reported in-band or out-of-band, which results in four combinations. Hence, the framework provides options to look at congestion cues beyond those reported by the receiver. We propose a sender-driven, a receiver-driven and a hybrid congestion control algorithm. The hybrid algorithm relies on both the sender and receiver co-operating to perform congestion control. Lastly, we compare the performance of these different algorithms. We also explore the idea of using capacity notifications from middleboxes (e.g., 3G/LTE base stations) along the path as cues for a congestion control algorithm. Further, we look at the interaction between error-resilience mechanisms and show that FEC can be used in a congestion control algorithm for probing for additional capacity. We propose Multipath RTP (MPRTP), an extension to RTP, which uses multiple paths for either aggregating capacity or for increasing error-resilience. We show that our proposed scheduling algorithm works in diverse scenarios (e.g., 3G and WLAN, 3G and 3G, etc.) with paths with varying latencies. Lastly, we propose a network coverage map service (NCMS), which aggregates throughput measurements from mobile users consuming multimedia services. The NCMS sends notifications to its subscribers about the upcoming network conditions, which take these notifications into account when performing congestion control. In order to test and refine the ideas presented in this thesis, we have implemented most of them in proof-of-concept prototypes, and conducted experiments and simulations to validate our assumptions and gain new insights.

Dynamic adaptive video streaming with minimal buffer sizes

Recently, adaptive streaming has been widely adopted in video streaming services to improve the Quality-of-Experience (QoE) of video delivery over the Internet. However, state-of-the-art bitrate adaptation achieves satisfactory performance only with extensive buffering of several tens of seconds. This leads to high playback latency in video delivery, which is undesirable especially in the context of live content with a low upper bound on the latency. Therefore, this thesis aims at pushing the application of adaptive streaming to its limit with respect to the buffer size, which is the dominant factor of the streaming latency. In this work, we first address the minimum buffering size required in adaptive streaming, which provides us with guidelines to determine a reasonable low latency for streaming systems. Then, we tackle the fundamental challenge of achieving such a low-latency streaming by developing a novel adaptation algorithm that stabilizes buffer dynamics despite a small buffer size. We also present advanced improvements by designing a novel adaptation architecture with low-delay feedback for the bitrate selection and optimizing the underlying transport layer to offer efficient realtime streaming. Experimental evaluations demonstrate that our approach achieves superior QoE in adaptive video streaming, especially in the particularly challenging case of low-latency streaming.In letzter Zeit setzen immer mehr Anbieter von Video-Streaming im Internet auf adaptives Streaming um die Nutzererfahrung (QoE) zu verbessern. Allerdings erreichen aktuelle Bitrate-Adaption-Algorithmen nur dann eine zufriedenstellende Leistung, wenn sehr große Puffer in der Größenordnung von mehreren zehn Sekunden eingesetzt werden. Dies führt zu großen Latenzen bei der Wiedergabe, was vor allem bei Live-Übertragungen mit einer niedrigen Obergrenze für Verzögerungen unerwünscht ist. Aus diesem Grund zielt die vorliegende Dissertation darauf ab adaptive Streaming-Anwendung im Bezug auf die Puffer-Größe zu optimieren da dies den Hauptfaktor für die Streaming-Latenz darstellt. In dieser Arbeit untersuchen wir zuerst die minimale benötigte Puffer-Größe für adaptives Streaming, was uns ermöglicht eine sinnvolle Untergrenze für die erreichbare Latenz festzulegen. Im nächsten Schritt gehen wir die grundlegende Herausforderung an dieses Optimum zu erreichen. Hierfür entwickeln wir einen neuartigen Adaptionsalgorithmus, der es ermöglicht den Füllstand des Puffers trotz der geringen Größe zu stabilisieren. Danach präsentieren wir weitere Verbesserungen indem wir eine neue Adaptions-Architektur für die Datenraten-Anpassung mit geringer Feedback-Verzögerung designen und das darunter liegende Transportprotokoll optimieren um effizientes Echtzeit-Streaming zu ermöglichen. Durch experimentelle Prüfung zeigen wir, dass unser Ansatz eine verbesserte Nutzererfahrung für adaptives Streaming erreicht, vor allem in besonders herausfordernden Fällen, wenn Streaming mit geringer Latenz gefordert ist