Computer Science

Permanent URI for this collectionhttps://hdl.handle.net/10679/43

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Now showing 1 - 14 of 14

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Automated adaptive playback for encoder-adjudicated live sports
(IEEE, 2022) Akgul, T.; Uğur, Deniz; Beğen, Ali Cengiz; Computer Science; BEĞEN, Ali Cengiz; Uğur, Deniz
In low-latency live streaming, it is not easy to simultaneously avoid stalls and maintain low latency. The trade-off needs to be decided in real time. One of the best tools for controlling the buffer level (hence, the stalls) and live latency is adaptive playback speed control, which slows down the playback when the buffer level is critically low to reduce the risk of stalling and speeds up the playback when the buffer is sufficiently full to reduce the live latency. Adaptive playback generally works well. However, it may introduce artifacts depending on the content. Viewers may be more sensitive to playback speed changes at certain scenes. In this paper, we augment the state-of-the-art content-aware playback speed control (CAPSC) algorithm by developing a post-encoder add-on tool that analyzes the encoded live content and automatically tags each output chunk with a value indicating its suitability for playback speed changes. The source code for the CAPSC algorithm and the new post-encoder add-on (developed for the snooker games) is publicly available.
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Bandwidth prediction in low-latency chunked streaming
(The ACM Digital Library, 2019-06) Bentaleb, A.; Timmerer, C.; Beğen, Ali Cengiz; Zimmermann, R.; Computer Science; BEĞEN, Ali Cengiz
HTTP adaptive streaming with chunked transfer encoding can be used to offer low-latency streaming without sacrificing the coding efficiency. While this allows a media segment to be generated and delivered at the same time, which is critical in reducing the latency, the conventional bitrate adaptation schemes make often grossly inaccurate bandwidth measurements due to the presence of idle periods between the chunks. These wrong measurements cause the streaming client to make bad adaptation decisions. To this end, we design ACTE, a new bitrate adaptation scheme that leverages the unique nature of chunk downloads. ACTE uses a sliding window to accurately measure the available bandwidth and an online linear adaptive filter to predict the bandwidth into the future. Results show that ACTE achieves 96% measurement accuracy, which translates to a 65% reduction in the number of stalls and a 49% increase in quality of experience on average compared to other schemes.
Open Access
Catching the moment with LoL + in twitch-like low-latency live streaming platforms
(IEEE, 2022) Bentaleb, A.; Akçay, Mehmet Necmettin; Lim, M.; Beğen, Ali Cengiz; Zimmermann, R.; Computer Science; BEĞEN, Ali Cengiz; Akçay, Mehmet Necmettin
Our earlier Low-on-Latency (dubbed as LoL) solution offered an accurate bandwidth prediction and rate adaptation algorithm tailored for live streaming applications that targeted an end-to-end latency of up to two seconds. While LoL was a significant step forward in multi-bitrate low-latency live streaming, further experimentation and testing showed that there was room for improvement in three areas. First, LoL used hard-coded parameters computed from an offline training process in the rate adaptation algorithm and this was seen as a significant barrier in LoL's wide deployment. Second, LoL's objective was to maximize a collective QoE function. Yet, certain use cases have specific objectives besides the singular QoE and this had to be accommodated. Third, the adaptive playback speed control failed to produce satisfying results in some scenarios. Our goal in this paper is to address these areas and make LoL sufficiently robust to deploy. We refer to the enhanced solution as LoL+ which has been integrated to the official dash.js player in v3.2.0.
Open Access
Common media client data (CMCD): Initial findings
(Association for Computing Machinery, Inc, 2021-07-16) Bentaleb, A.; Lim, M.; Akçay, Mehmet Necmettin; Beğen, Ali Cengiz; Zimmermann, R.; Computer Science; BEĞEN, Ali Cengiz; Akçay, Mehmet Necmettin
In September 2020, the Consumer Technology Association (CTA) published the CTA-5004: Common Media Client Data (CMCD) specification. Using this specification, a media client can convey certain information to the content delivery network servers with object requests. This information is useful in log association/analysis, quality of service/experience monitoring and delivery enhancements. This paper is the first step toward investigating the feasibility of CMCD in addressing one of the most common problems in the streaming domain: efficient use of shared bandwidth by multiple clients. To that effect, we implemented CMCD functions on an HTTP server and built a proof-of-concept system with CMCD-Aware dash.js clients. We show that even a basic bandwidth allocation scheme enabled by CMCD reduces rebuffering rate and duration without noticeably sacrificing the video quality.
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Content-aware playback speed control for low-latency live streaming of sports
(The ACM Digital Library, 2021) Aladağ, Ö. F.; Uğur, Deniz; Akçay, Mehmet Necmettin; Beğen, Ali Cengiz; Computer Science; BEĞEN, Ali Cengiz; Uğur, Deniz; Akçay, Mehmet Necmettin
There are two main factors that determine the viewer experience during the live streaming of sports content: latency and stalls. Latency should be low and stalls should not occur. Yet, these two factors work against each other and it is not trivial to strike the best trade-off between them. One of the best tools we have today to manage this trade-off is the adaptive playback speed control. This tool allows the streaming client to slow down the playback when there is a risk of stalling and increase the playback when there is no risk of stalling but the live latency is higher than desired. While adaptive playback generally works well, the artifacts due to the changes in the playback speed should preferably be unnoticeable to the viewers. However, this mostly depends on the portion of the audio/video content subject to the playback speed change. In this paper, we advance the state-of-the-art by developing a content-aware playback speed control (CAPSC) algorithm and demonstrate a number of examples showing its significance. We make the running code available and provide a demo page hoping that it will be a useful tool for the developers and content providers.
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Data-driven bandwidth prediction models and automated model selection for low latency
(IEEE, 2021) Bentaleb, A.; Beğen, Ali Cengiz; Harous, S.; Zimmermann, R.; Computer Science; BEĞEN, Ali Cengiz
Today's HTTP adaptive streaming solutions use a variety of algorithms to measure the available network bandwidth and predict its future values. Bandwidth prediction, which is already a difficult task, must be more accurate when lower latency is desired due to the shorter time available to react to bandwidth changes, and when mobile networks are involved due to their inherently more frequent and potentially larger bandwidth fluctuations. Any inaccuracy in bandwidth prediction results in flawed adaptation decisions, which will in turn translate into a diminished viewer experience. We propose an Automated Model for Prediction (AMP) that encompasses techniques for bandwidth prediction and model auto-selection specifically designed for low-latency live steaming with chunked transfer encoding. We first study statistical and computational intelligence techniques to implement a suite of bandwidth prediction models that can work accurately under a broad range of network conditions, and second, we introduce an automated prediction model selection method. We confirm the effectiveness of our solution through trace-driven live streaming experiments.
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Game of streaming players: Is consensus viable or an illusion?
(Association for Computing Machinery, Inc, 2019-08) Bentaleb, A.; Beğen, Ali Cengiz; Harous, S.; Zimmermann, R.; Computer Science; BEĞEN, Ali Cengiz
The dramatic growth of HTTP adaptive streaming (HAS) traffic represents a practical challenge for service providers in satisfying the demand from their customers. Achieving this in a network where multiple players share the network capacity has so far proved hard because of the bandwidth competition among the HAS players. This competition is exacerbated by the bandwidth overestimation that is introduced due to the isolated and selfish behavior of the HAS players. Each player strives individually to select the maximum bitrate without considering the co-existing players or network resource dynamics. As a result, the HAS players suffer from video quality instability, quality unfairness, and network underutilization or oversubscription, and the players observe a poor quality of experience (QoE). To address this issue, we propose a fully distributed game theory and consensus-based collaborative adaptive bitrate solution for shared network environments, termed Game Theory and consensus-based Approach for Cooperative HAS delivery systems (GTAC). Our solution consists of two-stage games that run in parallel during a streaming session. We extensively evaluate GTAC on a broad set of trace-driven and real-world experiments. Results show that GTAC enhances the viewer QoE by up to 22%, presentation quality stability by up to 24%, fairness by at least 31%, and network utilization by 28% compared to the well-known schemes.
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Game theory based bitrate adaptation for Dash.Js reference player
(IEEE, 2018-11-28) Bentaleb, A.; Beğen, Ali Cengiz; Zimmermann, R.; Computer Science; BEĞEN, Ali Cengiz
Most existing DASH adaptive bitrate (ABR) schemes are designed to behave in their own self-interest and do not perform consistently in all network environments. In this work, we provide a practical implementation, materials and demonstration of a game theoretical ABR scheme, termed GTA [1], in the dash.js reference player. The GTA approach optimizes the viewer experience across multiple players without requiring explicit communication, and maintains a high playback bitrate while reducing startup delay, and minimizing quality switches and stalls.
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Improving server and client-side algorithms for adaptive streaming of non-immersive and immersive media
(The ACM Digital Library,, 2021) Akçay, Mehmet Necmettin; Akçay, Mehmet Necmettin
HTTP adaptive streaming is a technique widely used in the internet today to stream live and on-demand content. Server and client-side algorithms play an important role in achieving a better user experience in terms of metrics such as latency, rebufferings and rendering quality. In this doctoral study, we propose and evaluate a number of new algorithms for both non-immersive and immersive media in different settings ranging from low-latency live to on-demand streaming.
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Metadata-based user interface design for enhanced content access and viewing
(The ACM Digital Library, 2020-05) Karmis, A. A.; Derya, A.; Beğen, Ali Cengiz; Computer Science; BEĞEN, Ali Cengiz
The nature of viewing is changing due to the huge volumes of content being produced including user content generated by amateurs and the proliferation of personalized services. The type of content being produced is not only for entertainment (movies/TV) purposes, but also can be instructional and directive (classroom, documentary and adult content). This leads to a type of viewing that is non-linear and requires increased random access into the content to be viewed effectively. Those who produce the content (or aggregate a number of existing ones) may not necessarily index it sufficiently for a variety of reasons. In-advance indexing would not work anyway in case the indexing used time-varying factors such as popularity, viewing frequency or duration. In this demo, we tackle this problem and present a new seekbar design for the dash.js player that allows the users to navigate the content more effectively and find the points of interest within the content faster. This new seekbar uses auxiliary metadata to show informative icons or color the parts of the media timeline differently to inform the users.
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Performance analysis of ACTE: A bandwidth prediction method for low-latency chunked streaming
(Association for Computing Machinery, Inc, 2020-07) Bentaleb, A.; Timmerer, C.; Beğen, Ali Cengiz; Zimmermann, R.; Computer Science; BEĞEN, Ali Cengiz
HTTP adaptive streaming with chunked transfer encoding can offer low-latency streaming without sacrificing the coding efficiency. This allows media segments to be delivered while still being packaged. However, conventional schemes often make widely inaccurate bandwidth measurements due to the presence of idle periods between the chunks and hence this is causing sub-optimal adaptation decisions. To address this issue, we earlier proposed ACTE (ABR for Chunked Transfer Encoding) [6], a bandwidth prediction scheme for low-latency chunked streaming. While ACTE was a significant step forward, in this study we focus on two still remaining open areas, namely, (i) quantifying the impact of encoding parameters, including chunk and segment durations, bitrate levels, minimum interval between IDR-frames and frame rate on ACTE, and (ii) exploring the impact of video content complexity on ACTE. We thoroughly investigate these questions and report on our findings. We also discuss some additional issues that arise in the context of pursuing very low latency HTTP video streaming.
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Quality upshifting with auxiliary I-Frame splicing
(IEEE, 2023) Akçay, Mehmet Necmettin; Kara, Burak; Beğen, Ali Cengiz; Ahsan, S.; Curcio, I. D. D.; Kammachi-Sreedhar, K.; Aksu, E.; Computer Science; BEĞEN, Ali Cengiz; Akçay, Mehmet Necmettin; Kara, Burak
This paper introduces the Auxiliary I-Frame Splicing method to reduce bandwidth waste in adaptive streaming. This method involves fetching a high-quality I-frame and splicing it into the already downloaded low-quality segment, resulting in a higher-quality rendering at a lower overhead than replacing the entire low-quality segment. In our experiments with three videos and four quantization parameters, the results show that the bandwidth can be saved up to 87% while still increasing the peak signal-to-noise ratio score by 20% and the video multi-method assessment fusion score by 73%. In the demo, we demonstrate the visual differences between the original and spliced videos.
Open Access
Take the red pill for H3 and see how deep the rabbit hole goes
(ACM, 2022-03-17) Nguyen, M.; Timmerer, C.; Pham, S.; Silhavy, D.; Beğen, Ali Cengiz; Computer Science; BEĞEN, Ali Cengiz
With the introduction of HTTP/3 (H3) and QUIC at its core, there is an expectation of significant improvements in Web-based secure object delivery. As HTTP is a central protocol to the current adaptive streaming methods in all major streaming services, an important question is what H3 will bring to the table for such services. To answer this question, we present the new features of H3 and QUIC, and compare them to those of H/1.1/2 and TCP. We also share the latest research findings in this domain.
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When they go high, we go low: low-latency live streaming in dash.js with LoL
(The ACM Digital Library, 2020-05) Lim, M.; Akçay, Mehmet Necmettin; Bentaleb, A.; Beğen, Ali Cengiz; Zimmermann, R.; Computer Science; BEĞEN, Ali Cengiz; Akçay, Mehmet Necmettin
Live streaming remains a challenge in the adaptive streaming space due to the stringent requirements for not just quality and rebuffering, but also latency. Many solutions have been proposed to tackle streaming in general, but only few have looked into better catering to the more challenging low-latency live streaming scenarios. In this paper, we re-visit and extend several important components (collectively called Low-on-Latency, LoL) in adaptive streaming systems to enhance the low-latency performance. LoL includes bitrate adaptation (both heuristic and learning-based), playback control and throughput measurement modules.

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