Improving Web Cache Performance via Adaptive Content Fragmentation Design

Abstract

The performance of web caches, in Web Content Management Systems, can be improved by assembling only some of the content elements of a web page in the application server, and finishing the assembling process in the cache proxy. Due to this, the cache is able to manage parts of the web page instead of whole pages, which improves its performance. We propose an algorithm based on decision trees and obtained in a training process to create content fragmentation designs. Data mining is used in the training phase. Inputs of the classification algorithm must be monitored from the system producing small overheads. The paper contribution are the validation of: the use of classification system to self-adapt content fragmentation designs to improve the web performance, the parameters set to be used as inputs of the decision tree and finally, the suitability of using decision trees to represent and implement, in the classification system, the previous extracted knowledge. All these aspects are validated by experimental results extracted from a test-bed.