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        Performance Engineering

        Learning Through Applications Using JMT

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        Author(s)
        Serazzi, Giuseppe
        Language
        English
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        Abstract
        This open access book improves the users' skills needed to implement models for performance evaluation of digital infrastructures. Building a model is usually a relatively easy task, but making it an accurate representation of the phenomenon to be reproduced is a completely different matter. It is well-known that to increase the ability to build reliable models it is necessary to accumulate experience. The book addresses this need by presenting a collection of case studies of increasing complexity. Readers are introduced to the modeling process gradually, learning the basic concepts step-by-step as they go through the case studies. Queueing Networks are used to design the models solved with simulation and analytical techniques from the open source Java Modelling Tools (JMT). Among the models analyzed there are systems for optimizing performance, identifying bottlenecks, evaluating the impact of the variability of traffic and service demands, analyzing the effects of synchronization policies in parallel computing. Four case studies derived from real-life scenarios are also presented: a surveillance system, autoscaling load fluctuations, web app workflow simulation, and crowd computing platform. This book serves as a reference tool for graduate and senior-level computer science students in courses of performance evaluation and modeling, as well as for researchers and practitioners.
        URI
        https://library.oapen.org/handle/20.500.12657/76735
        Keywords
        Capacity planning of digital infrastructures; Performance modeling; performance models; Petri Nets; Queueing Networks
        DOI
        10.1007/978-3-031-36763-2
        ISBN
        9783031367632, 9783031367632, 9783031367625
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        Cham, 2024
        Grantor
        • Politecnico di Milano - [...]
        Imprint
        Springer Nature Switzerland
        Pages
        146
        Rights
        http://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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