Web Server Performance Optimization using Prediction Prefetching Engine

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.

Predicting the Users' Navigation Patterns in Web, using Weighted Association Rules and Users' Navigation Information

“…Makker and Rathy In [12], using users' behavior analysis, an approach, which makes use of preprocessing of log-file, is presented in order to pre-fetch, predict, and improve the performance of the web server. Clustering, Marco Model, and association rules are the three techniques used in recommending webpages.…”

“…To this end, scores are calculated for all the pages the user has not visited so far. While determining the score of the suggestion, the rate of the correspondence between the user's current session with the mentioned association rules which were examined in relation (11), and the weighted confidence coefficient are calculated based on relation (12):…”

Mobile-based system for cost-effective e-learning contents delivery in resource and bandwidth constrained learning environments

“…Lujara (2008) proposed Compact Disk Read Only Memory (CD-ROM) for offline delivery; however this solution cannot accommodate the needs due to the rapid growth of the amount of information and the increased number of e-learning users. Furthermore, a client-side proxy architecture for supporting the offline use of learning contents and bracing approach for increasing the web server performance was suggested (Trifonova, 2006;Makker & Rathy, 2011). However, pre-fetching and caching contents to the local memory were done automatically by the system owing to filling the cache with documents without any prior knowledge of the user.…”