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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Shi, L., Gu, Z., Pei, Y., Wei, L. (2005). A PPM Prediction Model Based on Web Objects’ Popularity. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_15
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DOI: https://doi.org/10.1007/11540007_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
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