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A blueprint for system-level performance modeling of software-intensive embedded systems.

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Title: A blueprint for system-level performance modeling of software-intensive embedded systems.
Authors: Hendriks, Martijn, Basten, Twan, Verriet, Jacques, Brassé, Marco, Somers, Lou
Source: International Journal on Software Tools for Technology Transfer; Feb2016, Vol. 18 Issue 1, p21-40, 20p
Subject Terms: COMPUTER software, EMBEDDED computer systems, ESTIMATION theory, ENERGY consumption, JAVA programming language, PROGRAMMING languages, COMPUTER simulation
Abstract: Exploration of design alternatives and estimation of their key performance metrics such as latency and energy consumption is essential for making the proper design decisions in the early phases of system development. Often, high-level models of the dynamic behavior of the system are used for the analysis of design alternatives. Our work presents a blueprint for building efficient and re-usable models for this purpose. It builds on the well-known Y-chart pattern in that it gives more structure for the proper modeling of interaction on shared resources that plays a prominent role in software-intensive embedded systems. We show how the blueprint can be used to model a small yet illustrative example system with the Uppaal tool, and with the Java general-purpose programming language, and reflect on their respective strengths and weaknesses. The Java-based approach has resulted in a very flexible and fast discrete-event simulator with many re-usable components. It currently is used by TNO-ESI and Océ-Technologies B.V. for early model-based performance analysis that supports the design process for professional printing systems. [ABSTRACT FROM AUTHOR]
Copyright of International Journal on Software Tools for Technology Transfer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A blueprint for system-level performance modeling of software-intensive embedded systems.
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  Data: International Journal on Software Tools for Technology Transfer; Feb2016, Vol. 18 Issue 1, p21-40, 20p
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  Data: Exploration of design alternatives and estimation of their key performance metrics such as latency and energy consumption is essential for making the proper design decisions in the early phases of system development. Often, high-level models of the dynamic behavior of the system are used for the analysis of design alternatives. Our work presents a blueprint for building efficient and re-usable models for this purpose. It builds on the well-known Y-chart pattern in that it gives more structure for the proper modeling of interaction on shared resources that plays a prominent role in software-intensive embedded systems. We show how the blueprint can be used to model a small yet illustrative example system with the Uppaal tool, and with the Java general-purpose programming language, and reflect on their respective strengths and weaknesses. The Java-based approach has resulted in a very flexible and fast discrete-event simulator with many re-usable components. It currently is used by TNO-ESI and Océ-Technologies B.V. for early model-based performance analysis that supports the design process for professional printing systems. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal on Software Tools for Technology Transfer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10009-014-0340-3
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              Text: Feb2016
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