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Dataset for WWW landing pages webobject retrieval performance evaluation

This dataset describes data obtained from a multi-day World Wide Web (WWW) measurement campaign distributed internationally across multiple Amazon Web Service (AWS) datacentres. The Chrome web browser was controlled by the Selenium framework to make repetitive requests to several popular websites; t...

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Detalles Bibliográficos
Autor principal: Seeling, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118300/
https://www.ncbi.nlm.nih.gov/pubmed/32258285
http://dx.doi.org/10.1016/j.dib.2020.105429
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author Seeling, Patrick
author_facet Seeling, Patrick
author_sort Seeling, Patrick
collection PubMed
description This dataset describes data obtained from a multi-day World Wide Web (WWW) measurement campaign distributed internationally across multiple Amazon Web Service (AWS) datacentres. The Chrome web browser was controlled by the Selenium framework to make repetitive requests to several popular websites; the resulting webobjects were captured by a proxy server and details about them stored in the provided SQLite3 databases. A Python script is provided to evaluate the webobjects with respect to their configured as well as their actual expiration times, as part of our more detailed analysis that we provide in [1]. Researchers and practitioners can readily employ this dataset in their own research endeavours with little efforts for avenues of inquiry beyond webobject expiration times we described in [1], as we provide additional information about each webobject and each website visit during the measurement campaign time horizon.
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spelling pubmed-71183002020-04-06 Dataset for WWW landing pages webobject retrieval performance evaluation Seeling, Patrick Data Brief Computer Science This dataset describes data obtained from a multi-day World Wide Web (WWW) measurement campaign distributed internationally across multiple Amazon Web Service (AWS) datacentres. The Chrome web browser was controlled by the Selenium framework to make repetitive requests to several popular websites; the resulting webobjects were captured by a proxy server and details about them stored in the provided SQLite3 databases. A Python script is provided to evaluate the webobjects with respect to their configured as well as their actual expiration times, as part of our more detailed analysis that we provide in [1]. Researchers and practitioners can readily employ this dataset in their own research endeavours with little efforts for avenues of inquiry beyond webobject expiration times we described in [1], as we provide additional information about each webobject and each website visit during the measurement campaign time horizon. Elsevier 2020-03-14 /pmc/articles/PMC7118300/ /pubmed/32258285 http://dx.doi.org/10.1016/j.dib.2020.105429 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Seeling, Patrick
Dataset for WWW landing pages webobject retrieval performance evaluation
title Dataset for WWW landing pages webobject retrieval performance evaluation
title_full Dataset for WWW landing pages webobject retrieval performance evaluation
title_fullStr Dataset for WWW landing pages webobject retrieval performance evaluation
title_full_unstemmed Dataset for WWW landing pages webobject retrieval performance evaluation
title_short Dataset for WWW landing pages webobject retrieval performance evaluation
title_sort dataset for www landing pages webobject retrieval performance evaluation
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118300/
https://www.ncbi.nlm.nih.gov/pubmed/32258285
http://dx.doi.org/10.1016/j.dib.2020.105429
work_keys_str_mv AT seelingpatrick datasetforwwwlandingpageswebobjectretrievalperformanceevaluation