iDSL: Automated Performance Prediction and Analysis of Medical Imaging Systems

Freek van den Berg, Anne Katharina Ingrid Remke, Boudewijn R.H.M. Haverkort

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    6 Citations (Scopus)
    5 Downloads (Pure)

    Abstract

    System designers need to have insight in the response times of service systems to see if they meet performance requirements. We present a high-level evaluation technique to obtain the distribution of services completion times. It is based on a high-level domain-specific language that hides the underlying technicalities from the system designer. Under the hood, probabilistic real-time model checking technology is used iteratively to obtain precise bounds and probabilities. This allows reasoning about nondeterministic, probabilistic and real-time aspects in a single evaluation. To reduce the state spaces for analysis, we use two sampling methods (for measurements) that simplify the system model: (i) applying an abstraction on time by increasing the length of a (discrete) model time unit, and (ii) computing only absolute bounds by replacing probabilistic choices with non-deterministic ones. We use an industrial case on image processing of an interventional X-ray system to illustrate our approach.
    Original languageUndefined
    Title of host publicationProceedings of the 12th European Workshop on Computer Performance Engineering, EPEW 2015
    EditorsMarta Beltran, William Knottenbelt, Jeremy Bradley
    Place of PublicationBerlin
    PublisherSpringer
    Pages227-242
    Number of pages16
    ISBN (Print)978-3-319-23266-9
    DOIs
    Publication statusPublished - 30 Aug 2015

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    Volume9272
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Keywords

    • EWI-26292
    • IR-98152
    • METIS-314966

    Cite this

    van den Berg, F., Remke, A. K. I., & Haverkort, B. R. H. M. (2015). iDSL: Automated Performance Prediction and Analysis of Medical Imaging Systems. In M. Beltran, W. Knottenbelt, & J. Bradley (Eds.), Proceedings of the 12th European Workshop on Computer Performance Engineering, EPEW 2015 (pp. 227-242). (Lecture Notes in Computer Science; Vol. 9272). Berlin: Springer. https://doi.org/10.1007/978-3-319-23267-6_15
    van den Berg, Freek ; Remke, Anne Katharina Ingrid ; Haverkort, Boudewijn R.H.M. / iDSL: Automated Performance Prediction and Analysis of Medical Imaging Systems. Proceedings of the 12th European Workshop on Computer Performance Engineering, EPEW 2015. editor / Marta Beltran ; William Knottenbelt ; Jeremy Bradley. Berlin : Springer, 2015. pp. 227-242 (Lecture Notes in Computer Science).
    @inproceedings{1443350d972a4ebc93d88119bfe4ef8c,
    title = "iDSL: Automated Performance Prediction and Analysis of Medical Imaging Systems",
    abstract = "System designers need to have insight in the response times of service systems to see if they meet performance requirements. We present a high-level evaluation technique to obtain the distribution of services completion times. It is based on a high-level domain-specific language that hides the underlying technicalities from the system designer. Under the hood, probabilistic real-time model checking technology is used iteratively to obtain precise bounds and probabilities. This allows reasoning about nondeterministic, probabilistic and real-time aspects in a single evaluation. To reduce the state spaces for analysis, we use two sampling methods (for measurements) that simplify the system model: (i) applying an abstraction on time by increasing the length of a (discrete) model time unit, and (ii) computing only absolute bounds by replacing probabilistic choices with non-deterministic ones. We use an industrial case on image processing of an interventional X-ray system to illustrate our approach.",
    keywords = "EWI-26292, IR-98152, METIS-314966",
    author = "{van den Berg}, Freek and Remke, {Anne Katharina Ingrid} and Haverkort, {Boudewijn R.H.M.}",
    note = "10.1007/978-3-319-23267-6_15",
    year = "2015",
    month = "8",
    day = "30",
    doi = "10.1007/978-3-319-23267-6_15",
    language = "Undefined",
    isbn = "978-3-319-23266-9",
    series = "Lecture Notes in Computer Science",
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    van den Berg, F, Remke, AKI & Haverkort, BRHM 2015, iDSL: Automated Performance Prediction and Analysis of Medical Imaging Systems. in M Beltran, W Knottenbelt & J Bradley (eds), Proceedings of the 12th European Workshop on Computer Performance Engineering, EPEW 2015. Lecture Notes in Computer Science, vol. 9272, Springer, Berlin, pp. 227-242. https://doi.org/10.1007/978-3-319-23267-6_15

    iDSL: Automated Performance Prediction and Analysis of Medical Imaging Systems. / van den Berg, Freek; Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.

    Proceedings of the 12th European Workshop on Computer Performance Engineering, EPEW 2015. ed. / Marta Beltran; William Knottenbelt; Jeremy Bradley. Berlin : Springer, 2015. p. 227-242 (Lecture Notes in Computer Science; Vol. 9272).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    AB - System designers need to have insight in the response times of service systems to see if they meet performance requirements. We present a high-level evaluation technique to obtain the distribution of services completion times. It is based on a high-level domain-specific language that hides the underlying technicalities from the system designer. Under the hood, probabilistic real-time model checking technology is used iteratively to obtain precise bounds and probabilities. This allows reasoning about nondeterministic, probabilistic and real-time aspects in a single evaluation. To reduce the state spaces for analysis, we use two sampling methods (for measurements) that simplify the system model: (i) applying an abstraction on time by increasing the length of a (discrete) model time unit, and (ii) computing only absolute bounds by replacing probabilistic choices with non-deterministic ones. We use an industrial case on image processing of an interventional X-ray system to illustrate our approach.

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    van den Berg F, Remke AKI, Haverkort BRHM. iDSL: Automated Performance Prediction and Analysis of Medical Imaging Systems. In Beltran M, Knottenbelt W, Bradley J, editors, Proceedings of the 12th European Workshop on Computer Performance Engineering, EPEW 2015. Berlin: Springer. 2015. p. 227-242. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-23267-6_15