A QoE Perspective on HTTP/2 Server Push

Zimmermann, Torsten; Wolters, Benedikt; Hohlfeld, Oliver

doi:10.1145/3098603.3098604

Cited by 13 publications

(11 citation statements)

References 15 publications

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“…For both metrics, smaller values denote better PLT performance. Combined, these metrics provide a decent impression of both the quantitative and qualitative load performance of a webpage, though they are not necessarily strongly correlated with real user perceived performance [27,43,57]. While this can be considered a limitation of our study, conducting a full-factorial subjective evaluation of this magnitude is practically hard.…”

Section: Resultsmentioning

confidence: 99%

HTTP/2 Prioritization and its Impact on Web Performance

Wijnants

Marx

Quax

et al. 2018

Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18

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Web performance is a hot topic, as many studies have shown a strong correlation between slow webpages and loss of revenue due to user dissatisfaction. Front and center in Page Load Time (PLT) optimization is the order in which resources are downloaded and processed. The new HTTP/2 speciication includes dedicated resource prioritization provisions, to be used in tandem with resource multiplexing over a single, well-illed TCP connection. However, little is yet known about its application by browsers and its impact on page load performance.This article details an extensive survey of modern User Agent implementations, with the conclusion that the major vendors all approach HTTP/2 prioritization in widely diferent ways, from naive (Safari, IE, Edge) to complex (Chrome, Firefox). We investigate the performance efect of these discrepancies with a full-factorial experimental evaluation involving eight prioritization algorithms, two of-the-shelf User Agents, 40 realistic webpages, and ive heterogeneous (emulated) network conditions. We ind that in general the complex approaches yield the best results, while naive schemes can lead to over 25% slower median visual load times. Also, prioritization is found to matter most for heavy-weight pages. Finally, it is ascertained that achieving PLT optimizations via generic serverside HTTP/2 re-prioritization schemes is a non-trivial task and that their performance is inluenced by the implementation intricacies of individual browsers.

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Section: Resultsmentioning

confidence: 99%

HTTP/2 Prioritization and its Impact on Web Performance

Wijnants

Marx

Quax

et al. 2018

Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18

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“…1) [35,39]-potentially given its complex usage. In previous studies, we showed that Server Push can be easily used suboptimally in real-world deployments and hurt instead of improving performance [39,40]. These findings, as well as discussions among web and protocol engineers [7,23,26,28], highlight that the quest for optimal Server Push usage is far from being settled.…”

Section: Introductionmentioning

confidence: 93%

“…Still, PLT can be an over-or underapproximation [22], e.g., events may refer to items not in view, and some resources can be loaded by scripts afterward. Hence, PLT can fail to capture human perception [11,40]. SpeedIndex.…”

Section: Website Performance Metricsmentioning

confidence: 99%

“…Please note that we do not assume any additional delay on the servers, e.g., for additional fetches or disk access. For all evaluation settings, we follow settings used in previous work [40] and utilize browsertime [1] to automate Chromium 64 and replay each website in each setting for 31 times. If not stated otherwise, we show and discuss the median result of these repeated runs.…”

Section: Controlled Push Strategy Evaluationmentioning

confidence: 99%

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Is the web ready for HTTP/2 server push?

Zimmermann

Wolters

Hohlfeld

et al. 2018

Proceedings of the 14th International Conference on Emerging Networking EXperiments and Technologies

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HTTP/2 supersedes HTTP/1.1 to tackle the performance challenges of the modern Web. A highly anticipated feature is Server Push, enabling servers to send data without explicit client requests, thus potentially saving time. Although guidelines on how to use Server Push emerged, measurements have shown that it can easily be used in a suboptimal way and hurt instead of improving performance. We thus tackle the question if the current Web can make better use of Server Push. First, we enable real-world websites to be replayed in a testbed to study the effects of different Server Push strategies. Using this, we next revisit proposed guidelines to grasp their performance impact. Finally, based on our results, we propose a novel strategy using an alternative server scheduler that enables to interleave resources. This improves the visual progress for some websites, with minor modifications to the deployment. Still, our results highlight the limits of Server Push: a deep understanding of web engineering is required to make optimal use of it, and not every site will benefit.

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“…Biswal et al [42] showed that QUIC improves PLT in poor network conditions, but it does not provide significant improvements when the webpage contains many small objects. Zimmermann et al [43] studied how the HTTP/2 [8] serverpush improves the perceived PLT. They showed that serverpush does not always yield a better perceived performance, but can also degrades the performance.…”

Section: Related Workmentioning

confidence: 99%

Measuring Web Latency and Rendering Performance: Method, Tools, and Longitudinal Dataset

Asrese

Eravuchira²,

Bajpai

et al. 2019

IEEE Trans. Netw. Serv. Manage.

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This paper presents Webget, a measurement tool that measures web Quality of Service (QoS) metrics including the DNS lookup time, time to first byte (TTFB) and the download time. Webget also captures web complexity metrics such as the number and the size of objects that make up the website. We deploy the Webget test to measure the web performance of Google, YouTube, and Facebook from 182 SamKnows probes. Using a 3.5year-long (Jan 2014-Jul 2017) dataset, we show that the DNS lookup time of these popular Content Delivery Networks (CDNs) and the download time of Google have improved over time. We also show that the TTFB towards Facebook exhibits worse performance than the Google CDN. Moreover, we show that the number and the size of objects are not the only factors that affect the web download time. We observe that these webpages perform differently across regions and service providers. We also developed a web measurement system, WePR (Web Performance and Rendering) that measures the same web QoS and complexity metrics as Webget, but it also captures the web Quality of Experience (QoE) metrics such as rendering time. WePR has a distributed architecture where the component that measures the web QoS and complexity metrics is deployed on the SamKnows probe, while the rendering time is calculated on a central server. We measured the rendering performance of four websites. We show that in 80% of the cases, the rendering time of the websites is faster than the downloading time. The source code of the WePR system and the dataset is made publicly available.

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A QoE Perspective on HTTP/2 Server Push

Cited by 13 publications

References 15 publications

HTTP/2 Prioritization and its Impact on Web Performance

HTTP/2 Prioritization and its Impact on Web Performance

Is the web ready for HTTP/2 server push?

Measuring Web Latency and Rendering Performance: Method, Tools, and Longitudinal Dataset

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