Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31097
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: Data Mining, association rule, proxy server

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1087296

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2698

References:


[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