BOLA: Near-optimal bitrate adaptation for online videos

By Kevin Spiteri, Rahul Urgaonkar, Ramesh K. Sitaraman. IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, 2016

850 citations recorded by the source corpus.

Modern video players employ complex algorithms to adapt the bitrate of the video that is shown to the user. Bitrate adaptation requires a tradeoff between reducing the probability that the video freezes and enhancing the quality of the video shown to the user. A bitrate that is too high leads to frequent video freezes (i.e., rebuffering), while a bitrate that is too low leads to poor video quality. Video providers segment the video into short chunks and encode each chunk at multiple bitrates. The video player adaptively chooses the bitrate of each chunk that is downloaded, possibly choosing different bitrates for successive chunks. While bitrate adaptation holds the key to a good quality of experience for the user, current video players use ad-hoc algorithms that are poorly understood. We formulate bitrate adaptation as a utility maximization problem and devise an online control algorithm called BOLA that uses Lyapunov optimization techniques to minimize rebuffering and maximize video quality. We prove that BOLA achieves a time-average utility that is within an additive term O(1/V) of the optimal value, for a control parameter V related to the video buffer size. Further, unlike prior work, our algorithm does not require any prediction of available network bandwidth. We empirically validate our algorithm in a simulated network environment using an extensive collection of network traces. We show that our algorithm achieves near-optimal utility and in many cases significantly higher utility than current state-of-the-art algorithms. Our work has immediate impact on real-world video players and BOLA is part of the reference player implementation for the evolving DASH standard for video transmission.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/fa8ae3cece8b35bcb31cf64ec30e20ebc2139c94

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Citations in the corpus

Oboe: auto-tuning video ABR algorithms to network conditions (2018, methodology): “For instance, HYB and BOLA primarily maximize average bitrate subject to low rebuffering.”
Learning in situ: a randomized experiment in video streaming (2019, background): “…on matching the video bitrate to the network throughput [20,23,27], “buffer-based” algorithms that steer the duration of the playback buffer [18,38,39], and control-theoretic schemes that try to maximize expected QoE over a receding horizon, given the upcoming chunk sizes and a prediction of the…”
A variegated look at 5G in the wild: performance, power, and QoE implications (2021, methodology): “(1) Buffer-based: BBA [32] and BOLA [56] make bitrate decisions based on the buffer occupancy.”
A Survey on Bitrate Adaptation Schemes for Streaming Media Over HTTP (2019, background): “system significantly improves the bitrate decision of clientbased adaptation schemes like BOLA [67] and FastMPC [81], and it offers a 24% on average better viewer QoE compared”