BOLA: Near-Optimal Bitrate Adaptation for Online Videos
Kevin Spiteri, Rahul Urgaonkar, Ramesh K. Sitaraman

TL;DR
BOLA is an online bitrate adaptation algorithm for streaming videos that optimizes video quality while minimizing rebuffering, without needing network bandwidth prediction, and is proven to be near-optimal and widely adopted.
Contribution
We introduce BOLA, a novel Lyapunov optimization-based algorithm for bitrate adaptation that achieves near-optimal utility without bandwidth prediction, and demonstrate its effectiveness through theoretical analysis and real-world deployment.
Findings
BOLA achieves utility within O(1/V) of the optimal.
BOLA outperforms existing algorithms in simulations.
BOLA is adopted in production by major video providers.
Abstract
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 (rebuffers) and enhancing the quality of the video. A bitrate that is too high leads to frequent rebuffering, while a bitrate that is too low leads to poor video quality. Video providers segment videos into short segments and encode each segment at multiple bitrates. The video player adaptively chooses the bitrate of each segment to download, possibly choosing different bitrates for successive segments. We formulate bitrate adaptation as a utility-maximization problem and devise an online control algorithm called BOLA that uses Lyapunov optimization to minimize rebuffering and maximize video quality. We prove that BOLA achieves a time-average utility that is within an additive term…
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