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A PPM Prediction Model Based on Web Objects’ Popularity

  • Lei Shi
  • Zhimin Gu
  • Yunxia Pei
  • Lin Wei
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3614)

Abstract

Web prefetching technique is one of the primary solutions used to reduce Web access latency and improve the quality of service. This paper makes use of Zipf’s 1st law and Zipf’s 2nd law to model the Web objects’ popularity, where Zipf’s 1st law is employed to model the high frequency Web objects and 2nd law for the low frequency Web objects, and proposes a PPM prediction model based on Web objects’ popularity for Web prefetching. A performance evaluation of the model is presented using real server logs. Trace-driven simulation results show that not only the model is easily to be implemented, but also can achieve a high prediction precision at the cost of relative low storage complexity and network traffic.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Lei Shi
    • 1
    • 2
  • Zhimin Gu
    • 1
  • Yunxia Pei
    • 2
  • Lin Wei
    • 2
  1. 1.Department of Computer Science and EngineeringBeijing Institute of TechnologyBeijingChina
  2. 2.College of Information EngineeringZhengzhou UniversityZhengzhouChina

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