Improving the Performance of Proxy Server by Using Data Mining Technique
Authors: P. Jomsri
Abstract:
Currently, web usage make a huge data from a lot of user attention. In general, proxy server is a system to support web usage from user and can manage system by using hit rates. This research tries to improve hit rates in proxy system by applying data mining technique. The data set are collected from proxy servers in the university and are investigated relationship based on several features. The model is used to predict the future access websites. Association rule technique is applied to get the relation among Date, Time, Main Group web, Sub Group web, and Domain name for created model. The results showed that this technique can predict web content for the next day, moreover the future accesses of websites increased from 38.15% to 85.57 %. This model can predict web page access which tends to increase the efficient of proxy servers as a result. In additional, the performance of internet access will be improved and help to reduce traffic in networks.
Keywords: Association rule, proxy server, data mining.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1087296
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[1] S .Podlipnig, L. Boszormenyi, “A survey of web cache replacement
strategies,” ACM Comput Surv ,vol.35(4), pp.374–398, 2003.
[2] B. Davison, “A web caching primer,” IEEE Internet Computing
vol.5(4), pp.38–45,2001.
[3] P. Jomsri, P. Tantasanawong, “Hit Rate Improvement in Proxy System
using Data Mining Technique,” in Proc. National Conference on
Information Technology, Bangkok, 2006 .
[4] L. Qiong , N. F. Jeffrey, X. Wenwei, “Form-based proxy caching for
database backed web sites: keywords and functions,” VLDB J ,
vol.17(3), pp. 489–513 ,2008.
[5] G. Houtzager, C. Jacob, C. Williamson, “An evolutionary approach to
optimal web proxy cache placement,” in proc IEEE Congr Evolut
Comput ,2006.
[6] J. Aguilar, EL. Leis ,“A coherence-replacement protocol for web proxy
cache systems,” Int J Comput Appl , vol.28(1), pp. 12–18, 2006.
[7] T. Fagni , R. Perego, S. Silverti, and S. Orlando,“Boosting the
performance of web search engines: caching and prefetching query
results by exploiting historical usage data,” ACM Transactions on
Information Systems, Vol. 24(1), pp. 51–78, 2006.
[8] C.C. Kaya, G. Zhang, Y. Tan, and V.S. Mookerjee , “An admissioncontrol
technique for delay reduction in proxy caching,” Decision
Support Systems, vol. 46(2), pp.594–603, 2009.
[9] M. Sabegi, and M. Yaghmaee, “Using fuzzy logic to improve cache
replacement decisions,” IJCSNS International Journal of Computer
Science and Network Security, vol.6(3A), 2006.
[10] M.C. Calzarossa, and G. Valli, “A fuzzy Algorithm for web caching,”
Simulation Series Journal, vol. 35(4), pp. 630–636 ,2003.
[11] P. Venketesh, and R. Venkatesan, “A survey on applications of neural
networks and evolutionary techniques in web caching,” IETE Tech Rev,
vol. 26(3),pp. 171–180, 2009.
[12] H. Khalid, “A new cache replacement scheme based on back
propagation neural networks,” ACM SIGARCH Comput Archit News,
vol. 25(1), pp. 27–33, 1997.
[13] What is Squid?’’, Available at http://www.squid-cache.org/Intro/
[14] X. Chen, and Y. Wu. “Personalized Knowledge Discovery: Mining
Novel Association Rules from Text,” Available:
http://www.siam.org/meetings/sdm06/proceedings/067chenx.pdf