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Enhancements to Randomized Web Proxy Caching Algorithms Using Data Mining Classifier Model

  • P. Julian BenaditEmail author
  • F. Sagayaraj Fancis
  • A. M. James Raj
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 713)

Abstract

Web proxy caching system is an intermediary between the users and servers that tries to alleviate the loads on the servers by caching selective web pages, behaves as the proxy for the server, and services the requests that are made to the servers by the users. In this paper, the performance of a proxy system is measured by the number of hits at the proxy. The higher number of hits at the proxy server reflects the effectiveness of the proxy system. The number of hits is determined by the replacement policies chosen by the proxy systems. Traditional replacement policies that are based on time and size are reactive and do not consider the events that will possibly happen in the future. The outcomes of the paper are proactive strategies that augment the traditional replacement policies with data mining techniques. In this work, the performance of the randomized replacement policies such as LRU-C, LRU-S, HARM, and RRGVF are adapted by the data mining classifier based on the weight assignment policy. Experiments were conducted on various data sets. Hit ratio and byte hit ratio were chosen as parameters for performance.

Keywords

Web proxy caching Data mining classifier Weight assignment policy Randomized replacement 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • P. Julian Benadit
    • 1
    Email author
  • F. Sagayaraj Fancis
    • 2
  • A. M. James Raj
    • 2
  1. 1.Department of Computer Science Engineering, Faculty of Engineering, Kengeri campusCHRIST (Deemed To be University)BangloreIndia
  2. 2.Department of Computer Science and EngineeringPondicherry Engineering CollegePondicherryIndia

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