The week's pick
Random Articles
Reseach Article
Web Server Performance Optimization using Prediction Prefetching Engine
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 23 - Number 9 |
| Year of Publication: 2011 |
| Authors: Silky Makker, R.K Rathy |
10.5120/2980-3974
|
Silky Makker, R.K Rathy . Web Server Performance Optimization using Prediction Prefetching Engine. International Journal of Computer Applications. 23, 9 ( June 2011), 19-24. DOI=10.5120/2980-3974
Abstract
The long-term success of the World Wide Web depends on fast response time. People use the Web to access information from remote sites, but do not like to wait long for their results. The rapid growth in the amount of information and the number of users has lead to difficulty in providing effective response time for the web users and this increased web latency; resulting in decreased web performance. Although several proposals have been made for reducing this latency, like it can be improved by caching, the benefit of using it is rather limited owing to filling the cache with documents without any prior knowledge.Predictive caching becomes an attractive solution wherein the forthcoming page likely to be requested soon are predicted based on user access logs information and pre-fetched ,while the user is browsing the current display pages. As web page prediction gained its importance, This paper proposes a bracing approach for increasing web server performance by analyzing user behavior, in this pre-fetching and prediction is done by pre-processing the user access log and integrating the three techniques i.e. Clustering, Markov model and association rules which achieves better web page access prediction accuracy;This work also overcomes the limitation of path completion i.e. by extracting web site structure paths are completed,which helps in better prediction, decreasing access time of user and improving web performance.
References
- Network performance, available at http://en.wikipedia.org/wiki/Network_performance
- Pallis, G., Vakali, A., Pokorny, J: A Clustering-based Prefetching Scheme on a Web Cache Environment. Int. Journal Computers & Electrical Engineering, Elsevier, Vol. 34, Issue 4, pp. 309-323
- Venkata N. Padmanbhan. “Improving World Wide Web Latency”, Technical Report, Computer Science Division, University of California, Berkeley, CA, May, 1995.
- Khalil, F., Li, J. and Wang, H. (2007) 'Integrating Markov model with clustering for predicting web page accesses', Australian World Wide Web (AusWeb'07), Coffs Harbour, Australia, pp.63-74.
- Khalil, Faten (2008) Combining web data mining techniques for web page access prediction.
- Thesis (_PhD/Research)
- Cooley, R., Mobasher, B., and Srivastava, J. Data preparation for mining World Wide Web browsing patterns. Journal of Knowledge and Information Systems 1, 1 (1999).
- Venkata N. Padmanbhan. “Improving World Wide Web Latency”, Technical Report, Computer Science Division, University of California, Berkeley, CA, May, 1995
- Fan L., Cao P., and Jacobson Q., “Web prefetching between Low-Bandwidth Clients and proxies: potential and performance.” In Proceedingsof the Joint International Conference on Measurement and Modeling of Computer Systems., May 1999.
- P. Atzeni, G. Mecca, and P. Merialdo, “To Weave the Web,” Proc. 23rd Conf. Very Large Data Bases (VLDB ’97), pp. 206-215, Aug.1997,
- Payal Gulati, A.K. Sharma, Amit Goel, Jyoti Pandey, "A Novel Approach for Determining Next Page Access," icetet, pp.1109-1113, 2008 First International Conference on Emerging Trends in Engineering and Technology, 2008.
- Pitkov, J. and Piroli, P. “Mining Longest repeating Subsequences to predict world wide web surfing, Proc. USENIX Symp. On Internet Technologies and Systems, 1999.
- Liu, B., Hsu, W., and Ma, Y., “Integrating Classification and Association Mining”, Proc. of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998.
- Yang, Q., Li, T., Wang, K., “Building Association Rules Based Sequential Classifiers for Web Document Prediction”, journal of Data Mining and Knowledge Discovery, Netherland: Kluwer Academic Publisher, 2004.
- V. Padmanabhan and J. Mogul, “Using Predictive prefetching to improve World Wide Web latency”, ACM SIGCOMM Computer Comm. Rev., Vol. 26,no.3, July 1996.
- Sarukkai, R.R., “Link prediction and path analysis using Markov chain”,proc. of the 9th International World Wide Web Conference on Computer networks, 2000.
- Liu, F. Lu Z. “ Mining Association rules using clustering”,Intelligent Data Analysis, 2001.
- Cadez I., Heckerman D., MeekC. Symth P., and Whire S., “Visualization of Navigation Patterns on a website using Model Based Clustering”, March, 2002
- Kim, D., Adam, N. Alturi, V., Bieber, M. & Yesha, Y. “A clickstream - based collaborative filtering personalization model:Towards a better performance”,WIDM, 2004
- Po-Zung Chen, Chu-Hao Sun, Shih-Yang Yang, “Modeling and Analysis the Web Structure Using Stochastic Timed Petri Nets”, Journal of Software, Vol. 3, No. 8, November 2008.
- Payal Gulati, A.K. Sharma, Amit Goel, Jyoti Pandey, "A Novel Approach for Determining Next Page Access," icetet, pp.1109-1113, 2008 First International Conference on Emerging Trends in Engineering and Technology, 2008.
- Deshpande, M. and G. Karypis, 2004. Selective markov models for predicting web page accesses. ACM Transact. Internet Technol., 4: 163-184.
- R. Ng and J. Han, “CLARANS: A Method for Clustering Objects for Spatial Data Mining,” IEEE Trans.Knowledge and Data Eng., vol. 14, no. 5, pp. 1003-1016, Sept./Oct. 2002.
- Jiacun Wang: Timed Petri Nets, Theory and Application, Boston: Kluwer Academic Publishers, 1998.
Index Terms
Keywords