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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Shi, L., Gu, Z., Wei, L., Shi, Y.: Popularity-based Selective Markov Model. In: IEEE/WIC/ACM International Conference on Web Intelligence, Beijing, pp. 504–507 (2004)
Thomas, M.K., Darrel, D., Jeffrey, C.M.: Exploring the bounds of Web latency reduction from caching and prefetching. In: Proceedings of the USENIX Symposium on Internet Technologies and Systems, pp. 13–22. USENIX Association, California (1997)
Crovella, M., Barford, P.: The network effects of prefetching. In: Proceedings of the IEEE Conference on Computer and Communications, San Francisco, pp. 1232–1240 (1998)
Palpanas, T., Mendelzon, A.: Web prefetching using partial match prediction. In: Proceedings of Web Caching Workshop, San Diego, California (March 1999)
Pitkow, J., Pirolli, P.: Mining Longest Repeating Subsequences to Predict World Wide Web Surfing. In: Proc. Usenix Technical Conf., Usenix, pp. 139–150 (1999)
Busari, M., Williamson, C.: On the sensitivity of Web proxy cache performance to workload characteristics. In: IEEE INFOCOM, pp. 1225–1234 (2001)
Cleary, J.G., Witten, I.H.: Data compression using adaptive coding and partial string matching. IEEE Transactions on Communications 32(4), 396–402 (1984)
Breslau, L., Cao, P., Fan, L., Phillips, G., Shenker, S.: Web caching and Zipf-like distributions: evidence and implications. In: IEEE INFOCOM, pp. 126–134 (1999)
Lawrence Berkeley National Laboratory, URL: http://ita.ee.lbl.gov/
Computer Science Department, University of California, Berkeley, http://www.cs.berkeley.edu/logs/
Khan, J.I., Tao, Q.: Partial Prefetch for Faster Surfing in Composite Hypermedia. In: Proc. Usenix Symp. Internet Technologies and Systems, Usenix, pp. 13–24 (2001)
Mahanti, A.: Web Proxy Workload Characterization and Modeling, M.Sc. Thesis, Department of Computer Science, University of Saskatchewan (September 1999)
Busari, M., Williamson, C.: On the sensitivity of Web proxy cache performance to workload characteristics. In: IEEE INFOCOM, pp. 1225–1234 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/11540007_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
Online ISBN: 978-3-540-31828-6
eBook Packages: Computer ScienceComputer Science (R0)