Motivated by the technology division of a financial services firm, we study the problem of capacity planning and allocation for Web-based applications. The steady growth in Web traffic has affected the quality of service (QoS) as measured by response time (RT), for numerous e-businesses. In addition, the lack of understanding of system interactions and availability of proper planning tools has impeded effective capacity management. Managers typically make decisions to add server capacity on an ad hoc basis when systems reach critical response levels. Very often this turns out to be too late and results in extremely long response times and the system crashes. We present an analytical model to understand system interactions with the goal of making better server capacity decisions based on the results. The model studies the relationships and important interactions between the various components of a Web-based application using a continuous time Markov chain embedded in a queuing network as the basic framework. We use several structured aggregation schemes to appropriately represent a complex system, and demonstrate how the model can be used to quickly predict system performance, which facilitates effective capacity allocation decision making. Using simulation as a benchmark, we show that our model produces results within 5% accuracy at a fraction of the time of simulation, even at high traffic intensities. This knowledge helps managers quickly analyze the performance of the system and better plan server capacity to maintain desirable levels of QoS. We also demonstrate how to utilize a combination of dedicated and shared resources to achieve QoS using fewer servers.
Web-based computer applications connect the end-user with information via the internet. These applications typically operate in distributed computing environments, collecting and collating information from multiple computers that host databases or traditional computer applications. The increase in internet traffic is a clear reflection of the increase in demand for various web-based applications. Managers often find it essential to have the capability to predict performance of these systems in order to maintain service levels, as measured by response time. We present a generic discrete event simulation tool for modelling web-based application systems. Modelling information flow for decision making in such systems requires constructs not typically available in simulation software. We have developed several constructs that can be used in constructing models for various kinds of web-based applications. An example system is modelled using the tool, the impact of different variables (eg transaction volume) on the system performance is analysed and some preliminary insights are presented.
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