Abstract
As the Internet today grows together with user and content the Internettraffic also increases. The World Wide Web (WWW) is one of themost popular applications used on the Internet today, and with thisit experiences network congestion and overloading of the original webserver. To counter this growing issue web caches are used to reducenetwork traffic and web server requests between clients and web servers.Implementation, adoption and usage of web caches can be time consumingfor sysadmins but a necessity. In this paper we will explore the possibilitiesof automating the web caches using machine learning techniques to reducesysadmin workload and errors making web caches more adoptable.
As the Internet today grows together with user and content the Internettraffic also increases. The World Wide Web (WWW) is one of themost popular applications used on the Internet today, and with thisit experiences network congestion and overloading of the original webserver. To counter this growing issue web caches are used to reducenetwork traffic and web server requests between clients and web servers.Implementation, adoption and usage of web caches can be time consumingfor sysadmins but a necessity. In this paper we will explore the possibilitiesof automating the web caches using machine learning techniques to reducesysadmin workload and errors making web caches more adoptable.