Abstract
Web systems are becoming more and more popular. An efficiently working network system is the basis for the functioning of every enterprise. Performance models are powerful tools for performance prediction. The creation of performance models requires significant effort. In the article, we want to present various performance models of customer and Web systems. In particular, we want to examine a system behaviour related to different flow routes of clients in the system. Therefore we propose Queueing Petri Nets, the new modeling methodology for dealing with performance issues of production systems. We follow the simulation-based approach. We consider 25 different models to check performance. Then we evaluate them based on the proposed metrics. The validation results show that the model is able to predict the performance with a relative error lower than 20%. Our evaluation shows that prepared models can reduce the effort of production system preparation. The resulting performance model can predict the system behaviour in a particular layer at the indicated load.
Highlights
Job scheduling, number of nodes, initial marking and many other parameters are the high importance in many computing systems, such as grid systems or cluster systems
We presented an architecture for online environments
The architecture is based on nodes and layers, which are responsible for modeling certain aspects of a system
Summary
Number of nodes, initial marking and many other parameters are the high importance in many computing systems, such as grid systems or cluster systems Their performance is directly related to the efficiency of the Web computing systems. The main aim of this research is the development of the method to predict the customer performance of the Web system by using Queueing Petri Net (QPN) that models and simulates environment. We propose a method for analyzing the performance of Web systems. We use Queueing Petri Net Modeling Environment (QPME) software [3] to study parameters of systems widespread in Web systems. The main idea is to allow a hierarchical model specification to reduce the model size This method is highly flexible and low-cost. We proposed a kind of potential application of this method to bigger structure consumer-to-business interactions [2,5]
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