Web Request Predictions

7 pages•Published: March 13, 2019

Randy Appleton, Ben Slater, Connor Laitinen, Luke Ammel and Cody Malnor

Abstract

If one could predict future web requests, it would be possible to make the web much faster. One could fetch web resources before they are needed. When the human user clicks on a link, the needed data would already have been downloaded.
We have created several algorithms that attempt to predict future web requests based on past histories. Our research evaluates and compares these prediction algorithms against real histories of web usage. Prediction algorithm results are compared based on correct predictions, erroneous predictions, and prediction rate.
Some algorithms make predictions rarely but accurately, while others may predict more often but with less accuracy. To take full advantage of this, we combine multiple algorithms and use different voting strategies to determine the best prediction.

Keyphrases: http/2.0, prefecthing web requests, prefetching

In: Gordon Lee and Ying Jin (editors). Proceedings of 34th International Conference on Computers and Their Applications, vol 58, pages 203-209.

Links:	https://easychair.org/publications/paper/Dmsm
	https://doi.org/10.29007/h63w

BibTeX entry

@inproceedings{CATA2019:Web_Request_Predictions,
  author    = {Randy Appleton and Ben Slater and Connor Laitinen and Luke Ammel and Cody Malnor},
  title     = {Web Request Predictions},
  booktitle = {Proceedings of 34th International Conference on Computers and Their Applications},
  editor    = {Gordon Lee and Ying Jin},
  series    = {EPiC Series in Computing},
  volume    = {58},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/Dmsm},
  doi       = {10.29007/h63w},
  pages     = {203-209},
  year      = {2019}}

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