A Granular Approach for Analyzing the Degree of Affability of a Web Site

Hochsztain, Esther; Millán, Socorro; Ruiz, Ernestina Menasalvas

doi:10.1007/3-540-45813-1_63

Cited by 1 publication

(1 citation statement)

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“…On this scenario, the quality of the services, or at least the way the user observes how these services are been performed, depends on some characteristics of the web server itself. Subjective values, like page design, are tackled by specific methodologies [16]. But, there are other factors that are also very important in terms of client satisfaction when he/she navigates the site.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Methods to Estimate Future Load in Web Farms

Peña

Robles

Marbán

et al. 2004

Advances in Web Intelligence

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Web Farms are clustered systems designed to provide high availability and high performance web services. A web farm is a group of replicated HTTP servers that reply web requests forwarded by a single point of access to the service. To deal with this task the point of access executes a load balancing algorithm to distribute web request among the group of servers. The present algorithms provides a short-term dynamic configuration for this operation, but some corrective actions (granting different session priorities or distributed WAN forwarding) cannot be achieved without a long-term estimation of the future web load. On this paper we propose a method to forecast web service work load. Our approach also includes an innovative segmentation method for the web pages using EDAs (estimation of distribution algorithms) and the application of semi-naïve Bayes classifiers to predict future web load several minutes before. All our analysis has been performed using real data from a world-wide academic portal.

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Section: Introductionmentioning

confidence: 99%