BOLA: Near-Optimal Bitrate Adaptation for Online Videos

Spiteri, Kevin; Urgaonkar, Rahul; Sitaraman, Ramesh K.

doi:10.1109/tnet.2020.2996964

Cited by 253 publications

(77 citation statements)

References 16 publications

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“…The performance of the proposed system is compared with the existing systems, Dash.js, BOLA, 6 and PANDA 7 . We examine the requested bitrate, the corresponding PSNR, and buffer states, as shown in Figures 10 to 12, respectively.…”

Section: Resultsmentioning

confidence: 99%

Congestion‐aware HTTP adaptive streaming system over SDN‐enabled Wi‐Fi network

Noh

Lee

et al. 2019

Concurrency and Computation

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This paper proposes a novel congestion-aware HTTP adaptive streaming (HAS) system to improve video quality of clients over software-defined network (SDN)-enabled Wi-Fi network. The proposed system employs SDN technology to efficiently control the network resources and video quality over the competing Wi-Fi network. In the proposed system, an SDN-enabled access point (AP) can monitor the streaming status of clients, such as the buffered playback time and information of requested segments. An SDN controller collects not only the streaming status of clients but also the Wi-Fi network conditions from the AP using OpenFlow. Additionally, when a congestion is going to occur, it determines the segment bitrate of each client to provide seamless and high-quality streaming services. The proposed system is fully implemented using open-source programs, such as ONOS and hostapd, and is examined in a real Wi-Fi network. The experimental results verify that the proposed system can provide seamless and high-quality HAS services for the clients compared with existing systems.

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Section: Resultsmentioning

confidence: 99%

Congestion‐aware HTTP adaptive streaming system over SDN‐enabled Wi‐Fi network

Noh

Lee

et al. 2019

Concurrency and Computation

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“…However, most of the papers study the video quality adaptation problem in the framework of HTTP Adaptive Streaming (HAS) [39]. For example, a well-known algorithm is proposed in [41]. This algorithm is implemented in Dash.js, a reference opensource video player for the MPEG-DASH technology [42].…”

Section: A Video Quality Adaptationmentioning

confidence: 99%

Adaptive Cloud-Based Extended Reality: Modeling and Optimization

et al. 2021

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Extended Reality (XR)-which includes Virtual Reality and Augmented Reality-promises to bring the virtual and telepresence experience to another level. Unfortunately, solutions leveraging these technologies require special high-performance computing platforms that degrade the cost-benefit balance. Moving processing to the cloud solves this problem but imposes strict requirements on data transmission reliability, bandwidth, and delays. The satisfaction of these requirements becomes an extremely challenging problem in the presence of other types of delay-sensitive traffic, such as remote control, industrial automation, or the control commands of the Cloud XR application itself. This article studies the joint service of the adaptive Cloud XR traffic with other high-priority delay-sensitive traffics. The paper develops an analytical model of the considered communication system. The model represents the system as a discrete state Markov chain and estimates the quality of experience for Cloud XR users in various scenarios. Using the model, the paper estimates the network capacity for the Cloud XR traffic and optimizes the bitrate adaptation function of the Cloud XR video streaming application. The goal of the optimization is to improve the visual quality of the virtual environment observed by the users, subject to the constrained probability of image impairments due to excessive delivery delays. Numerical results demonstrate the high accuracy of the developed model and the benefits provided by the optimization. INDEX TERMS Cloud XR, heterogeneous traffic, high-priority traffic, real-time adaptive video, virtual reality, quality of experience, queueing systems, analytical models, Markov chain.

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“…In the buffer-based approach, the video quality is proportional to the buffer occupancy. A few studies have addressed the bufferbased approach to model the playback buffer [16][17][18][19][20]. BBA performs rate adaptation using a function that linearly maps the current buffer occupancy to the video bitrate [21].…”

Section: Rate Adaptation Schemesmentioning

confidence: 99%

Buffer-based rate adaptation scheme for HTTP video streaming with consistent quality

2021

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Recently, HyperText Transfer Protocol (HTTP) based adaptive streaming (HAS) has been proposed as a solution for efficient use of network resources. HAS performs rate adaptation that adjusts the video quality according to the network conditions. The conventional approaches for rate adaptation involve accurately estimating the available bandwidth or exploiting the playback buffer in HAS clients rather than estimating the network bandwidth. In this paper, we present a playback buffer model for rate adaptation and propose a new buffer-based rate adaptation scheme. First, we model the playback buffer as a queueing system that stores video segments. The proposed scheme selects the next video bitrate that minimizes the difference between the current buffer occupancy and the expected value from the playback buffer model. The evaluation results indicated that the proposed scheme achieves higher video quality than conventional algorithms and can cope with various environments without the tuning of the configuration parameters.

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BOLA: Near-Optimal Bitrate Adaptation for Online Videos

Cited by 253 publications

References 16 publications

Congestion‐aware HTTP adaptive streaming system over SDN‐enabled Wi‐Fi network

Congestion‐aware HTTP adaptive streaming system over SDN‐enabled Wi‐Fi network

Adaptive Cloud-Based Extended Reality: Modeling and Optimization

Buffer-based rate adaptation scheme for HTTP video streaming with consistent quality

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