A Hybrid P2P/Multi-Server Quality-Adaptive Live-Streaming Solution Enhancing End-User's QoE

Bruneau-Queyreix, Joachim; Lacaud, Mathias; Negru, Daniel

doi:10.1145/3123266.3127936

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…Roverso et al have proposed a peer-to-peer-based approach that supports HTTPbased live streaming and has comparable performance to CDNs by using proactive-reactive hybrid prefetching [52]. Bruneau et al have proposed a mechanism to download chunks both from multiple peers and dedicated servers [10]. In contrast, Evensen et al [17] proposed using 3G and WiFi to improve the quality of live streams.…”

Section: Related Workmentioning

confidence: 99%

Playing chunk-transferred DASH segments at low latency with QLive

Yadav

Bentaleb

Lim

et al. 2021

Proceedings of the 12th ACM Multimedia Systems Conference

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More users have a growing interest in low latency over-the-top (OTT) applications such as online video gaming, video chat, online casino, sports betting, and live auctions. OTT applications face challenges in delivering low latency live streams using Dynamic Adaptive Streaming over HTTP (DASH) due to large playback buffer and video segment duration. A potential solution to this issue is the use of HTTP chunked transfer encoding (CTE) with the common media application format (CMAF). This combination allows the delivery of each segment in several chunks to the client, starting before the segment is fully available in real-time. However, CTE and CMAF alone are not sufficient as they do not address other limitations and challenges at the client-side, including inaccurate bandwidth measurement, latency control, and bitrate selection.In this paper, we leverage a simple and intuitive method to resolve the fundamental problem of bandwidth estimation for low latency live streaming through the use of a hybrid of an existing chunk parser and proposed filtering of downloaded chunk data. Next, we model the playback buffer as a / /1/ queue to limit the playback delay. The combination of these techniques is collectively called QLive. QLive uses the relationship between the estimated bandwidth, total buffer capacity, instantaneous playback speed, and buffer occupancy to decide the playback speed and the bitrate of the representation to download. We evaluated QLive under a diverse set of scenarios and found that it controls the latency to meet the given latency requirement, with an average latency up to 21 times lower than the compared methods. The average playback speed of QLive ranges between 1.01 -1.26× and it plays back at 1× speed up to 97% longer than the compared algorithms, without sacrificing the quality of the video. Moreover, the proposed bandwidth estimator has a 94% accuracy and is unaffected by a spike in instantaneous playback latency, unlike the compared state-of-the-art counterparts.

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Section: Related Workmentioning

confidence: 99%