Analyzing the Long Range Dependence and Object Popularity in Evaluating the Performance of Web Caching

Abstract

Web cache systems enhance Web services by reducing the client side latency. To deploy an effective Web cache, analysis of the traffic characteristics is indispensable. Various reported results of traffic analysis show evidences of long range dependence (LRD) in the data stream and rank distribution of the documents in Web traffic. This article analyzes Web cache traffic properties like LRD and rank distribution based on the traces collected from NLANR (National Laboratory of Applied Network Research) cache servers. Traces are processed to investigate the performance of Web cache servers and traffic patterns. Statistical tools are utilized to measure the strengths of the LRD and popularity. The Hurst parameter, which is a measure of the LRD, is estimated using various statistical methods. It is observed that the presence of LRD in the traffic is feeble and does not influence the Web cache performance.