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

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

G.P. Sajeev (Government Engineering College - Kozhikode, India) and M.P. Sebastian (National Institute of Technology - Calicut, India)
DOI: 10.4018/jitwe.2009100602
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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.
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Web caching is emerged as a technique to leverage the quality of Web services (Barish & Obraczka, 2000). In spite of the evolution of new caching schemes and algorithms, the performance of cache services never reached to the expected levels, as can be seen from Table 1, 2 and 3. Suitable setting of the cache performance parameters can provide a solution to this problem. Hit ratio, byte-hit ratio, client side latency and network load reduction (server side and network) are some important cache performance parameters. These parameters can be estimated by analyzing the input traffic stream and Web proxy traces.

Table 1.
Traces used
TraceDateNumber of requestsHit RatioZipf slope
NLANR-pa1 'st Sep 20072,80,06236%0.72
NLANR-pa1 'st Oct 20072,10,73432%0.76
NLANR-bo210'th Aug 20072,43,35626%0.69
NLANR-sj9'th Jan 20075,44,35620%0.80
Internet Traffic Archive23 'rd Jan 200528,33848%0.72
Table 2.
Summary statistics of on May 2007
HTTP Requests25227623815611442610935691362111475734269663
Hit rate (docs)42%31%35%8%18%18%40%
MEAN Obj Size10255157221863642719116033280112569
MB served (all)246735712033445521507461643232
MB served cache2152431662651672850263
Percent Savings9%7%8%6%5%6%8%

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