Web-log mining for predictive web caching
Qiang Yang, H.H. Zhang
Abstract
Qiang Yang, H.H. Zhang
Abstract
Caching is a well-known strategy for improving the performance of Web-based systems. The heart of a caching system is its page replacement policy, which selects the pages to be replaced in a cache when a request arrives. In this paper, we present a Web-log mining method for caching Web objects and use this algorithm to enhance the performance of Web caching systems. In our approach, we develop an n-gram-based prediction algorithm that can predict future Web requests. The prediction model is then used to extend the well-known GDSF caching policy. We empirically show that the system performance is improved using the predictive-caching approach.
OpenAlex reports 76 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Caching is a well-known strategy for improving the performance of Web-based systems. The heart of a caching system is its page replacement policy, which selects the pages to be replaced in a cache when a request arrives. In this paper, we present a Web-log mining method for caching Web objects and use this algorithm to enhance the performance of Web caching systems. In our approach, we develop an n-gram-based prediction algorithm that can predict future Web requests. The prediction model is then used to extend the well-known GDSF caching policy. We empirically show that the system performance is improved using the predictive-caching approach.
Key concepts: Computer science, Cache, Web page, Web mining, Data Web, Static web page, Web navigation, False sharing