Q-AIMD: A Congestion Aware Video Quality Control Mechanism

Following the constant increase of the multimedia traffic, it seems necessary to allow transport protocols to be aware of the video quality of the transmitted flows rather than the throughput. This paper proposes a novel transport mechanism adapted to video flows. Our proposal, called Q-AIMD for video quality AIMD (Additive Increase Multiplicative Decrease), enables fairness in video quality while transmitting multiple video flows. Targeting video quality fairness allows improving the overall video quality for all transmitted flows, especially when the transmitted videos provide various types of content with different spatial resolutions. In addition, Q-AIMD mitigates the occurrence of network congestion events, and dissolves the congestion whenever it occurs by decreasing the video quality and hence the bitrate. Using different video quality metrics, Q-AIMD is evaluated with different video contents and spatial resolutions. Simulation results show that Q-AIMD allows an improved overall video quality among the multiple transmitted video flows compared to a throughput-based congestion control by decreasing significantly the quality discrepancy between them

Region of interest-based adaptive multimedia streaming scheme

Adaptive multimedia streaming aims at adjusting the transmitted content based on the available bandwidth such as losses that often severely affect the end-user perceived quality are minimized and consequently the transmission quality increases. Current solutions affect equally the whole viewing area of the multimedia frames, despite research showing that there are regions on which the viewers are more interested in than on others. This paper presents a novel region of interest-based adaptive scheme (ROIAS) for multimedia streaming that when performing transmission-related quality adjustments, selectively affects the quality of those regions of the image the viewers are the least interested in. As the quality of the regions the viewers are the most interested in will not change (or will involve little change),the proposed scheme provides higher overall end-user perceived quality than any of the existing adaptive solutions

Video TFRC

TCP-friendly rate control (TFRC) is a congestion control technique that trade-offs responsiveness to the network conditions for a smoother throughput variation. We take advantage of this trade-off by calculating the rate gap between the theoretical TCP throughput and the smoothed TFRC throughput. Any rate gain from this rate gap is then opportunistically used for video coding. We define a frame complexity measure to determine the additional rate to be used from the rate gap and then perform a rate negotiation to determine the target rate for the encoder and the final sending rate. Results show that although this method has a more aggressive sending rate compared to TFRC, it is still TCP friendly, does not contribute too much to network congestion and achieves a reasonable video quality gain over the conventional method

Congestion-Aware Scalable Video Streaming

Postprin

The QUIC Fix for Optimal Video Streaming

Within a few years of its introduction, QUIC has gained traction: a significant chunk of traffic is now delivered over QUIC. The networking community is actively engaged in debating the fairness, performance, and applicability of QUIC for various use cases, but these debates are centered around a narrow, common theme: how does the new reliable transport built on top of UDP fare in different scenarios? Support for unreliable delivery in QUIC remains largely unexplored. The option for delivering content unreliably, as in a best-effort model, deserves the QUIC designers' and community's attention. We propose extending QUIC to support unreliable streams and present a simple approach for implementation. We discuss a simple use case of video streaming---an application that dominates the overall Internet traffic---that can leverage the unreliable streams and potentially bring immense benefits to network operators and content providers. To this end, we present a prototype implementation that, by using both the reliable and unreliable streams in QUIC, outperforms both TCP and QUIC in our evaluations.Comment: Published to ACM CoNEXT Workshop on the Evolution, Performance, and Interoperability of QUIC (EPIQ

System Support for Bandwidth Management and Content Adaptation in Internet Applications

This paper describes the implementation and evaluation of an operating system module, the Congestion Manager (CM), which provides integrated network flow management and exports a convenient programming interface that allows applications to be notified of, and adapt to, changing network conditions. We describe the API by which applications interface with the CM, and the architectural considerations that factored into the design. To evaluate the architecture and API, we describe our implementations of TCP; a streaming layered audio/video application; and an interactive audio application using the CM, and show that they achieve adaptive behavior without incurring much end-system overhead. All flows including TCP benefit from the sharing of congestion information, and applications are able to incorporate new functionality such as congestion control and adaptive behavior.Comment: 14 pages, appeared in OSDI 200