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 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 for the evolving DASH standard for video transmission.

QoE-Assured 4K HTTP Live Streaming via Transient Segment Holding at Mobile Edge

“…Generally, the common practice to avoid buffering is to perform video quality adaptation, where a number of wellknown algorithms such as FESTIVE [11], PANDA [12] and BOLA [13] have been proposed in this context. However, in the RAN+backhaul scenario that this paper focuses on, the poor E2E TCP throughput means downgrading video quality is inevitable from time to time, which would cause deteriorated QoE.…”

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

“…A high bitrate causes recurrent video freezing (i.e., buffer underrun), while a low bitrate leads to degraded video quality. Bitrate adaptation was considered as a utility maximization issue and algorithm BOLA (Buffer Occupancy based Lyapunov Algorithm) [67] was devised to optimize rebuffering enabling acceptable video quality. Two key performance parameters that influence the over quality of users scrutinized: (a) average quality of playback over a stipulated time that depends on the supplied bitrates of video chunks and (b) the amount of time to wait before rebuffering.…”

“…This methodology of BOLA disagrees with bitrate adaptation algorithms employed in general, which provides limited flexibility. The work of [67] evaluated adaptive and generic streaming with mobile vehicular environments and exposed that when bandwidth reduces, the quality adaptation technique can adequately decrease the stalling by 80% and enable a superior usage of the accessible bandwidth at the time when bandwidth enhances. Moreover, they declared HAS to be effective even in static environments, as it removes the majority of the stalling by switching the quality.…”

Improving Video Quality in Crowded Networks Using a DANE

“…We con rm performance problems (video/playback freezes and frequently changing video quality) of two established adaptation algorithms (throughputbased and Bu er Occupancy-based Lyapunov Algorithm (BOLA) [20]) in a real network with up to 600 concurrent DASH players. We propose a solution using network assisted DASH which seeks to facilitate more DASH players in a network and to improve the viewers' QoE.…”