WePR: A Tool for Automated Web Performance Measurement

IEEE Trans. Netw. Serv. Manage.

Eravuchira²,

Bajpai

et al. 2019

Self Cite

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.

Section: A Samknows Probementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

IEEE Trans. Netw. Serv. Manage.

Eravuchira²,

Bajpai

et al. 2019

Self Cite

“…We extended our measurement tool -WePR [2], to capture the web performance and end-user browsing experience in MBB networks. The tool measures the web communication latency metrics such as DNS lookup time, TCP connection time, HTTP download time, and the web complexity metrics including number of HTTP(S) elements, the size and type of the object.…”

Section: Experiments Designmentioning

confidence: 99%

Poster abstract: Measuring web latency in cellular networks

IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

Walelgne

Lutu

et al. 2018

Self Cite

This work presents a new methodology to measure the performance of web browsing over operational Mobile Broadband (MBB) networks. We designed a web performance measurement tool that collects both the web QoS metrics and the web rendering time in a browser window. We used MONROE [1], European wide measurement platform, to deploy our tool and to conduct a web browsing measurement over operational MBB networks. The results from the initial deployment show that different operators across countries and within the same country have a significant difference in web browsing performance (e.g. in the median case TIM is 75 ms faster than I WIND regarding time to first byte (TTFB)).

Measuring Web Quality of Experience in Cellular Networks

Passive and Active Measurement

Walelgne

Bajpai

et al. 2019

Self Cite

I am immensely thankful to my families and relatives for their unconditional love and support through my school life. Last but not least, I would like to thank my better half, Ichalem, for her love and everything else. This thesis is dedicated to my mother Tena Yihunie -who is my role model of perseverance and confidence -and Adisualem -youngest brother, who was born three weeks after this research was started.