Understanding the impact of video quality on user engagement

Dobrian, Florin; Sekar, Vyas; Awan, Asad; Stoica, Ion; Joseph, Denny; Ganjam, Aditya; Zhan, Jibin; Zhang, Hui

doi:10.1145/2018436.2018478

Cited by 504 publications

(308 citation statements)

References 22 publications

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“…This case of multi-homed content-i.e., content that is served by multiple CDNs-requires an additional request mapping layer to route requests to CDNs selected for delivery [15,20,30]. A Meta-CDN service can be provided by third-party infrastructures, most prominently Conviva for video delivery [2,13] and Cedexis for general (web) services [1,17,30]. Within these Meta-CDNs, the request mapping function of a participating content provider is unknown.…”

Section: Background and Related Workmentioning

confidence: 99%

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Dissecting Apple's Meta-CDN during an iOS Update

Blendin¹,

Bendfeldt

Poese³

et al. 2018

Proceedings of the Internet Measurement Conference 2018

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Content delivery networks (CDN) contribute more than 50% of today's Internet traffic. Meta-CDNs, an evolution of centrally controlled CDNs, promise increased flexibility by multihoming content. So far, efforts to understand the characteristics of Meta-CDNs focus mainly on third-party Meta-CDN services. A common, but unexplored, use case for Meta-CDNs is to use the CDNs mapping infrastructure to form self-operated Meta-CDNs integrating thirdparty CDNs. These CDNs assist in the build-up phase of a CDN's infrastructure or mitigate capacity shortages by offloading traffic. This paper investigates the Apple CDN as a prominent example of self-operated Meta-CDNs. We describe the involved CDNs, the request-mapping mechanism, and show the cache locations of the Apple CDN using measurements of more than 800 RIPE Atlas probes worldwide. We further measure its load-sharing behavior by observing a major iOS update in Sep. 2017, a significant event potentially reaching up to an estimated 1 billion iOS devices. Furthermore, by analyzing data from a European Eyeball ISP, we quantify thirdparty traffic offloading effects and find third-party CDNs increase their traffic by 438% while saturating seemingly unrelated links.

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Section: Background and Related Workmentioning

confidence: 99%

“…Known instances of third-party Meta-CDNs [15,22,23,30] provide services to implement custom and dynamic request mapping policies to direct traffic to the different CDNs. The characteristics of third-party Meta-CDNs have been studied in part on the example of Conviva [2,13,22] and Cedexis [17] as the prevalent operators.…”

Section: Introductionmentioning

confidence: 99%

Dissecting Apple's Meta-CDN during an iOS Update

Blendin¹,

Bendfeldt

Poese³

et al. 2018

Proceedings of the Internet Measurement Conference 2018

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“…It is noteworthy that the rate adaptation logic of clients is not specified in the DASH protocol. Naive DASH adaptation logics usually suffer from large quality variations or playback buffer underflow [3], which drastically deteriorates the quality of experience (QoE) of users [4]. Because the network bandwidth is highly dynamic, it is challenging to provide stable and high quality videos to ensure satisfactory user experience all the time.…”

Section: Introductionmentioning

confidence: 99%

An Ensemble Rate Adaptation Framework for Dynamic Adaptive Streaming Over HTTP

Yuan

Hou

et al. 2020

IEEE Trans. on Broadcast.

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Rate adaptation is one of the most important issues in dynamic adaptive streaming over HTTP (DASH). Due to the frequent fluctuations of the network bandwidth and complex variations of video content, it is difficult to deal with the varying network conditions and video content perfectly by using a single rate adaptation method. In this paper, we propose an ensemble rate adaptation framework for DASH, which aims to leverage the advantages of multiple methods involved in the framework to improve the quality of experience (QoE) of users. The proposed framework is simple yet very effective. Specifically, the proposed framework is composed of two modules, i.e. the method pool and method controller. In the method pool, several rate adaptation methods are integrated. At each decision time, only the method that can achieve the best QoE is chosen to determine the bitrate of the requested video segment. Besides, we also propose two strategies for switching methods, i.e., InstAnt Method Switching, and InterMittent Method Switching, for the method controller to determine which method can provide the best QoEs. Simulation results demonstrate that, the proposed framework always achieves the highest QoE for the change of channel environment and video complexity, compared with stateof-the-art rate adaptation methods.

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“…• Video freezes caused by rebuffering: Dobrian et al [11] show that rebuffering has the largest impact on user engagement. Conviva [10] estimates the number of HAS sessions that suffer from video freezes at 27 percent.…”

Section: Introductionmentioning

confidence: 99%

HTTP/2-Based Methods to Improve the Live Experience of Adaptive Streaming

Huysegems¹,

Hooft

Bostoen³

et al. 2015

Proceedings of the 23rd ACM International Conference on Multimedia

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HTTP Adaptive Streaming (HAS) is today the number one video technology for over-the-top video distribution. In HAS, video content is temporally divided into multiple segments and encoded at different quality levels. A client selects and retrieves per segment the most suited quality version to create a seamless playout. Despite the ability of HAS to deal with changing network conditions, HAS-based live streaming often suffers from freezes in the playout due to buffer under-run, low average quality, large camera-to-display delay, and large initial/channel-change delay. Recently, IETF has standardized HTTP/2, a new version of the HTTP protocol that provides new features for reducing the page load time in Web browsing. In this paper, we present ten novel HTTP/2-based methods to improve the quality of experience of HAS. Our main contribution is the design and evaluation of a push-based approach for live streaming in which super-short segments are pushed from server to client as soon as they become available. We show that with an RTT of 300 ms, this approach can reduce the average server-todisplay delay by 90.1 % and the average start-up delay by 40.1 %.

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Understanding the impact of video quality on user engagement

Cited by 504 publications

References 22 publications

Dissecting Apple's Meta-CDN during an iOS Update

Dissecting Apple's Meta-CDN during an iOS Update

An Ensemble Rate Adaptation Framework for Dynamic Adaptive Streaming Over HTTP

HTTP/2-Based Methods to Improve the Live Experience of Adaptive Streaming

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