A Multi-Dimensional Approach to Understanding the Effect of Page Content and Infrastructure on Page Load Time
Resumo
We study the metric Page Load Time (PLT) which has a significant impact on user experience, search engine optimization, and conversion rates. We explore how page complexity metrics, specifically content and infrastructure, affect PLT. We employ both supervised and unsupervised machine learning models to analyze the influence of these metrics at multiple levels: single page, page category, cluster, and general. Our study shows that the number of bytes, requests, and distinct images are key features in PLT prediction, with the page category model generally outperforming others. The results contribute to a better understanding of the factors influencing PLT and show some insights into how to optimize web pages for better user experiences and business outcomes.
Referências
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Avram, C., Salem, K., and Wong, B. (2014). Latency amplification: Characterizing the impact of web page content on load times. Lecture Notes in Computer Science, pages 20–25.
Butkiewicz, M., Madhyastha, H. V., and Sekar, V. (2011). Understanding website complexity: measurements, metrics, and implications. IMC ’11: Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference, page 313–328.
Egger, S., Reichl, P., Hoßfeld, T., and Schatz, R. (2012). ”time is bandwidth”? narrowing the gap between subjective time perception and quality of experience. 2012 IEEE International Conference on Communications, pages 1325–1330.
Gao, Q., Dey, P., and Ahammad, P. (2017). Perceived performance of top retail webpages in the wild: Insights from large-scale crowdsourcing of above-the-fold qoe. Internet QoE ’17: Proceedings of the Workshop on QoE-based Analysis and Management of Data Communication, page 13–18.
Gigspaces (July, 2023). Amazon found every 100ms of latency cost them 1% in sales. [link], Accessed: 2024-01-12.
Google (April, 2010). Using site speed in web search ranking. [link], Accessed: 2024-01-12.
Hora, D. D., Asrese, A. S., Christophides, V., Teixeira, R., and Rossi, D. (2018). Narrowing the gap between qos metrics and web qoe using above-the-fold metrics. PAM 2018 - International Conference on Passive and Active Network Measurement, pages 1–13.
Hoßfeld, T., Metzger, F., and Rossi, D. (2018). Speed index: Relating the industrial standard for user perceived web performance to web qoe. 2018 Tenth International Conference on Quality of Multimedia Experience, pages 1–6.
Huet, A., Saverimoutou, A., Houidi, Z. B., Shi, H., Cai, S., Xu, J., and Mathieu, B. (2021). Deployable models for approximating web qoe metrics from encrypted traffic. IEEE Transactions on Network and Service Management, 13:3336–3352.
Jahromi, H. Z., Delaney, D. T., and Hines, A. (2018). How crisp is the crease? a subjective study on web browsing perception of above-the-fold. 2020 6th IEEE Conference on Network Softwarization, pages 43–50.
Molnar, C. (2019). Interpretable Machine Learning. [link].
Salutari, F., Hora, D. D., Dubuc, G., and Rossi, D. (2019). A large-scale study of wikipedia users’ quality of experience. WWW ’19: The World Wide Web Conference, page 3194–3200.
Saverimoutou, A., Mathieu, B., and Vaton, S. (2019). A 6-month analysis of factors impacting web browsing quality for qoe prediction. Computer Networks, 164.
Vogel, L. and Springer, T. (2022). An in-depth analysis of web page structure and efficiency with focus on optimization potential for initial page load. International Conference on Web Engineering, pages 101–116.
Wiegand (April, 2022). Site speed is (still) impacting your conversion rate. [link], Accessed: 2024-01-12.
Asrese, A. S., Eravuchira, S. J., Bajpai, V., and Sarolahti, P. (2019). Measuring web latency and rendering performance: Method, tools, and longitudinal dataset. IEEE Transactions on Network and Service Management, 16:535–549.
Avram, C., Salem, K., and Wong, B. (2014). Latency amplification: Characterizing the impact of web page content on load times. Lecture Notes in Computer Science, pages 20–25.
Butkiewicz, M., Madhyastha, H. V., and Sekar, V. (2011). Understanding website complexity: measurements, metrics, and implications. IMC ’11: Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference, page 313–328.
Egger, S., Reichl, P., Hoßfeld, T., and Schatz, R. (2012). ”time is bandwidth”? narrowing the gap between subjective time perception and quality of experience. 2012 IEEE International Conference on Communications, pages 1325–1330.
Gao, Q., Dey, P., and Ahammad, P. (2017). Perceived performance of top retail webpages in the wild: Insights from large-scale crowdsourcing of above-the-fold qoe. Internet QoE ’17: Proceedings of the Workshop on QoE-based Analysis and Management of Data Communication, page 13–18.
Gigspaces (July, 2023). Amazon found every 100ms of latency cost them 1% in sales. [link], Accessed: 2024-01-12.
Google (April, 2010). Using site speed in web search ranking. [link], Accessed: 2024-01-12.
Hora, D. D., Asrese, A. S., Christophides, V., Teixeira, R., and Rossi, D. (2018). Narrowing the gap between qos metrics and web qoe using above-the-fold metrics. PAM 2018 - International Conference on Passive and Active Network Measurement, pages 1–13.
Hoßfeld, T., Metzger, F., and Rossi, D. (2018). Speed index: Relating the industrial standard for user perceived web performance to web qoe. 2018 Tenth International Conference on Quality of Multimedia Experience, pages 1–6.
Huet, A., Saverimoutou, A., Houidi, Z. B., Shi, H., Cai, S., Xu, J., and Mathieu, B. (2021). Deployable models for approximating web qoe metrics from encrypted traffic. IEEE Transactions on Network and Service Management, 13:3336–3352.
Jahromi, H. Z., Delaney, D. T., and Hines, A. (2018). How crisp is the crease? a subjective study on web browsing perception of above-the-fold. 2020 6th IEEE Conference on Network Softwarization, pages 43–50.
Molnar, C. (2019). Interpretable Machine Learning. [link].
Salutari, F., Hora, D. D., Dubuc, G., and Rossi, D. (2019). A large-scale study of wikipedia users’ quality of experience. WWW ’19: The World Wide Web Conference, page 3194–3200.
Saverimoutou, A., Mathieu, B., and Vaton, S. (2019). A 6-month analysis of factors impacting web browsing quality for qoe prediction. Computer Networks, 164.
Vogel, L. and Springer, T. (2022). An in-depth analysis of web page structure and efficiency with focus on optimization potential for initial page load. International Conference on Web Engineering, pages 101–116.
Wiegand (April, 2022). Site speed is (still) impacting your conversion rate. [link], Accessed: 2024-01-12.
Publicado
20/05/2024
Como Citar
OLIVEIRA, Daniel A.; LEÃO, Rosa M. M.; SOUZA E SILVA, Edmundo de.
A Multi-Dimensional Approach to Understanding the Effect of Page Content and Infrastructure on Page Load Time. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 42. , 2024, Niterói/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 756-769.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2024.1470.
