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BOLA: Near-Optimal Bitrate Adaptation for Online Videos | IEEE Journals & Magazine | IEEE Xplore

BOLA: Near-Optimal Bitrate Adaptation for Online Videos


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 pr...Show More

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 O(1/V) of the optimal value, for a control parameter V related to the video buffer size. Further, unlike prior work, BOLA does not require prediction of available network bandwidth. We empirically validate BOLA in a simulated network environment using a collection of network traces. We show that BOLA 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 for the evolving DASH standard for video transmission. We also implemented an updated version of BOLA that is now part of the standard reference player dash.js and is used in production by several video providers such as Akamai, BBC, CBS, and Orange.
Published in: IEEE/ACM Transactions on Networking ( Volume: 28, Issue: 4, August 2020)
Page(s): 1698 - 1711
Date of Publication: 08 June 2020

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I. Introduction

Online videos are the “killer” application of the Internet with videos currently accounting for more than half of the Internet traffic. Video viewership is growing at a torrid pace and videos are expected to account for more than 85% of all Internet traffic within a few years [2]. As all forms of traditional media migrate to the Internet, video providers face the daunting challenge of providing a good quality of experience (QoE) for users watching their videos. Video providers are diverse and include major media companies (e.g., NBC, CBS), news outlets (e.g., CNN), sports organizations (e.g., NFL, MLB), and video subscription services (e.g., Netflix, Hulu). Recent research has shown that low-performing videos that start slowly, play at lower bitrates, and freeze frequently can cause viewers to abandon the videos or watch fewer minutes of the videos, significantly decreasing the opportunity for generating revenue for the video providers [3]–[5], underscoring the need for a high-quality user experience.

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