SURFING THE WEB USING BROWSER INTERFACE FALILITIES: A PERFORMANCE EVALUATION APPROACH

The user interaction with the current web contents is a major concern when defining web workloads in order to precisely estimate system performance. However, the intrinsic difficulty to represent this dynamic behavior with a workload model has caused that many research studies are still using non representative workloads of the current web navigations. In contrast, in previous works we demonstrated that the use of an accurate workload model which considers user's dynamism when navigating the web clearly affects system performance metrics. In this paper we analyze, for the first time, the effect of considering the User-Browser Interaction as a part of user's dynamic behavior on web workload characterization in performance studies. To this end, we evaluate a typical e-commerce scenario and compare the obtained results for different behaviors that take the user interaction into account, such as the use of the back button and parallel browsing originated by using browser tabs or opening new windows when surfing a website. Experimental results show that these interaction patterns allow users to achieve their navigation objectives sooner, so increasing their productivity up to 200% when surfing the Web. In addition, results prove that when this type of navigations is taken into account, performance indexes can widely differ and relax the stress borderline of the server. For instance, the server utilization drops as much as 45% due to parallel browsing behavior.