B. A. de la Ossa, J.A. Gil, J. Sahuquillo, A. Pont
{"title":"Improving Web Prefetching by Making Predictions at Prefetch","authors":"B. A. de la Ossa, J.A. Gil, J. Sahuquillo, A. Pont","doi":"10.1109/NGI.2007.371193","DOIUrl":null,"url":null,"abstract":"Most of the research attempts to improve Web prefetching techniques have focused on the prediction algorithm with the objective of increasing its precision or, in the best case, to reduce the user's perceived latency. In contrast, to improve prefetching performance, this work concentrates in the prefetching engine and proposes the Prediction at Prefetch (P@P) technique. This paper explains how a prefetching technique can be extended to include our P@P proposal on real world conditions without changes in the web architecture or HTTP protocol. To show how this proposal can improve prefetching performance an extensive performance evaluation study has been done and the results show that P@P can considerably reduce the user's perceived latency with no additional cost over the basic prefetch mechanism.","PeriodicalId":207883,"journal":{"name":"2007 Next Generation Internet Networks","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Next Generation Internet Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NGI.2007.371193","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Most of the research attempts to improve Web prefetching techniques have focused on the prediction algorithm with the objective of increasing its precision or, in the best case, to reduce the user's perceived latency. In contrast, to improve prefetching performance, this work concentrates in the prefetching engine and proposes the Prediction at Prefetch (P@P) technique. This paper explains how a prefetching technique can be extended to include our P@P proposal on real world conditions without changes in the web architecture or HTTP protocol. To show how this proposal can improve prefetching performance an extensive performance evaluation study has been done and the results show that P@P can considerably reduce the user's perceived latency with no additional cost over the basic prefetch mechanism.