PhD Dissertations
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Browsing by Author "Akçay, Mehmet Necmettin"
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PhD DissertationPublication Metadata only Server and client-side algorithms for enhancing adaptive streamingAkçay, Mehmet Necmettin; Beğen, Ali Cengiz; Beğen, Ali Cengiz; Arı, İsmail; Civanlar, Mehmet Reha; Sayıt, M.; Akgül, T.; Department of Computer Science; Akçay, Mehmet NecmettinHTTP adaptive video streaming is a technique widely used on the internet today to stream live and on-demand content. Server and client-side algorithms play an important role in improving user experience in terms of metrics such as latency, rebufferings and rendering quality. After explaining the commonly used metrics, we analyzed four main aspects of video streaming (i) bandwidth prediction accuracy, (ii) utilization of playback speed, (iii) adaptive streaming for content-aware-encoded videos, and (iv) head motion awareness for 360-degree videos. 360-degree video streaming requires much higher bandwidth compared to conventional video streaming. We demonstrate that most of the algorithmic improvements achieved for video streaming can also be applied to Viewport Dependent Streaming (VDS) for 360-degree videos. It is also important that in 360-degree video streaming, we have a Head Mounted Display (HMD) device that is capable of pointing the viewport orientation of the user. We also investigate and improve the rate-adaptation algorithms for 360-degree videos by developing several new algorithms making use of the HMD. The new algorithms proposed in this thesis are Low-on-Latency (LoL), Low-on-Latency+ (LoL+), Bang-on-Bandwidth (BoB), Size-aware Rate Adaptation (SARA), Content-aware Playback Speed Control (CAPSC), Head-motion-aware Viewport Margins (HMAVM).We evaluate the proposed new algorithms using the objective metrics discussed in detail and show significant contributions for these new algorithms including up to 91% decrease in rebuffering duration for on-demand streaming, 61.9% decrease in rebuffering duration and 8.1% decrease in latency compared to L2A for low-latency live streaming, 81.3% bandwidth prediction accuracy for interactive streaming, lastly 20% improvement in viewport quality and 50% reduction in motion-to-high-quality delay for 360-degree video streaming.