By the same authors

Validating High Level Simulation Results against Experimental Data and Low Level Simulation: A Case Study

Research output: Contribution to conference › Paper › peer-review

Standard

Validating High Level Simulation Results against Experimental Data and Low Level Simulation : A Case Study. / Griffin, David Jack; Harbin, James Robert; Burns, Alan; Bate, Iain John; Davis, Robert Ian; Soares Indrusiak, Leandro.

2019. Paper presented at Real-Time Networks and Systems, Toulouse, France.

Research output: Contribution to conference › Paper › peer-review

Harvard

Griffin, DJ, Harbin, JR, Burns, A, Bate, IJ, Davis, RI & Soares Indrusiak, L 2019, 'Validating High Level Simulation Results against Experimental Data and Low Level Simulation: A Case Study', Paper presented at Real-Time Networks and Systems, Toulouse, France, 6/11/19 - 8/11/19. https://doi.org/10.1145/3356401.3356414

APA

Griffin, D. J., Harbin, J. R., Burns, A., Bate, I. J., Davis, R. I., & Soares Indrusiak, L. (2019). Validating High Level Simulation Results against Experimental Data and Low Level Simulation: A Case Study. Paper presented at Real-Time Networks and Systems, Toulouse, France. https://doi.org/10.1145/3356401.3356414

Vancouver

Griffin DJ, Harbin JR, Burns A, Bate IJ, Davis RI, Soares Indrusiak L. Validating High Level Simulation Results against Experimental Data and Low Level Simulation: A Case Study. 2019. Paper presented at Real-Time Networks and Systems, Toulouse, France. https://doi.org/10.1145/3356401.3356414

Author

Griffin, David Jack ; Harbin, James Robert ; Burns, Alan ; Bate, Iain John ; Davis, Robert Ian ; Soares Indrusiak, Leandro. / Validating High Level Simulation Results against Experimental Data and Low Level Simulation : A Case Study. Paper presented at Real-Time Networks and Systems, Toulouse, France.

Bibtex - Download

@conference{6d2ce52b1a2a4f18920ff328c926fa04,
title = "Validating High Level Simulation Results against Experimental Data and Low Level Simulation: A Case Study",
abstract = "Simulation can be considered a necessary evil in the validation ofsystems, especially when the system under consideration is beingprototyped and therefore does not presently exist. This is compounded by the use of high level simulators; on the one hand, highlevel simulation is efficient, in that it abstracts away many detailsof the system which are deemed to be not important. This allowsfor a simpler and faster running simulator, which allows the userto obtain results faster and/or perform more experiments. On theother hand, some of the details abstracted away might turn out tobe important, introducing inaccuracies.This paper outlines a framework for the statistical understandingand attribution of the errors produced by a high level simulatorwhen compared against real experiments by means of a low levelsimulator. This allows the user of a simulator to determine whetheror not the inaccuracies are significant, and whether or not the highlevel simulator requires refinements in its accuracy for the resultsto be valid. These techniques are illustrated via a case study.",
author = "Griffin, {David Jack} and Harbin, {James Robert} and Alan Burns and Bate, {Iain John} and Davis, {Robert Ian} and {Soares Indrusiak}, Leandro",
note = "{\textcopyright} 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. This is an author-produced version of the published paper. Uploaded in accordance with the publisher{\textquoteright}s self-archiving policy. Further copying may not be permitted; contact the publisher for details. ; Real-Time Networks and Systems, RTNS ; Conference date: 06-11-2019 Through 08-11-2019",
year = "2019",
month = aug,
day = "1",
doi = "10.1145/3356401.3356414",
language = "English",

}

RIS (suitable for import to EndNote) - Download

TY - CONF

T1 - Validating High Level Simulation Results against Experimental Data and Low Level Simulation

T2 - Real-Time Networks and Systems

AU - Griffin, David Jack

AU - Harbin, James Robert

AU - Burns, Alan

AU - Bate, Iain John

AU - Davis, Robert Ian

AU - Soares Indrusiak, Leandro

N1 - © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

PY - 2019/8/1

Y1 - 2019/8/1

N2 - Simulation can be considered a necessary evil in the validation ofsystems, especially when the system under consideration is beingprototyped and therefore does not presently exist. This is compounded by the use of high level simulators; on the one hand, highlevel simulation is efficient, in that it abstracts away many detailsof the system which are deemed to be not important. This allowsfor a simpler and faster running simulator, which allows the userto obtain results faster and/or perform more experiments. On theother hand, some of the details abstracted away might turn out tobe important, introducing inaccuracies.This paper outlines a framework for the statistical understandingand attribution of the errors produced by a high level simulatorwhen compared against real experiments by means of a low levelsimulator. This allows the user of a simulator to determine whetheror not the inaccuracies are significant, and whether or not the highlevel simulator requires refinements in its accuracy for the resultsto be valid. These techniques are illustrated via a case study.

AB - Simulation can be considered a necessary evil in the validation ofsystems, especially when the system under consideration is beingprototyped and therefore does not presently exist. This is compounded by the use of high level simulators; on the one hand, highlevel simulation is efficient, in that it abstracts away many detailsof the system which are deemed to be not important. This allowsfor a simpler and faster running simulator, which allows the userto obtain results faster and/or perform more experiments. On theother hand, some of the details abstracted away might turn out tobe important, introducing inaccuracies.This paper outlines a framework for the statistical understandingand attribution of the errors produced by a high level simulatorwhen compared against real experiments by means of a low levelsimulator. This allows the user of a simulator to determine whetheror not the inaccuracies are significant, and whether or not the highlevel simulator requires refinements in its accuracy for the resultsto be valid. These techniques are illustrated via a case study.

U2 - 10.1145/3356401.3356414

DO - 10.1145/3356401.3356414

M3 - Paper

Y2 - 6 November 2019 through 8 November 2019

ER -

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