Distributing scenario-based models: A replicate-and-project approach

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

  • Shlomi Steinberg
  • Joel Greenyer
  • Daniel Gritzner
  • David Harel
  • Guy Katz
  • Assaf Marron

Research Organisations

External Research Organisations

  • Weizmann Institute of Science
  • Stanford University
View graph of relations

Details

Original languageEnglish
Title of host publicationMODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development
EditorsLuis Ferreira Pires, Slimane Hammoudi, Bran Selic
Pages182-195
Number of pages14
ISBN (electronic)9789897582103
Publication statusPublished - 2017
Event5th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2017 - Porto, Portugal
Duration: 19 Feb 201721 Feb 2017

Publication series

NameMODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development
Volume2017-January

Abstract

In recent years, scenario-based modeling has been proposed to help mitigate some of the underlying difficulties in modeling complex reactive systems, by allowing modelers to specify system behavior in a way that is intuitive and directly executable. This modeling approach simplifies the specification of systems that include events occurring in distinct system components. However, when these system components are physically distributed, executing the scenario-based model requires inter-component coordination that may negatively affect system performance or robustness. We describe a technique that aims to reduce the amount of joint eventselection decisions that require coordination and synchronization among distributed system components. The technique calls for replicating the entire scenario-based executable specification in each of the components, and then transforming it in a component-specific manner that induces the required differences in execution while reducing synchronization requirements. In addition to advantages in streamlining design and improving performance, our approach captures the fact that in certain "smart" distributed systems it is often required that components know what rules govern the behavior of other components. Our evaluation of the technique shows promising results.

Keywords

    Concurrency, Distributed systems, Scenario-based modeling, Software engineering

ASJC Scopus subject areas

Cite this

Distributing scenario-based models: A replicate-and-project approach. / Steinberg, Shlomi; Greenyer, Joel; Gritzner, Daniel et al.
MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development. ed. / Luis Ferreira Pires; Slimane Hammoudi; Bran Selic. 2017. p. 182-195 (MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development; Vol. 2017-January).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Steinberg, S, Greenyer, J, Gritzner, D, Harel, D, Katz, G & Marron, A 2017, Distributing scenario-based models: A replicate-and-project approach. in LF Pires, S Hammoudi & B Selic (eds), MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development. MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development, vol. 2017-January, pp. 182-195, 5th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2017, Porto, Portugal, 19 Feb 2017. https://doi.org/10.5220/0006271301820195
Steinberg, S., Greenyer, J., Gritzner, D., Harel, D., Katz, G., & Marron, A. (2017). Distributing scenario-based models: A replicate-and-project approach. In L. F. Pires, S. Hammoudi, & B. Selic (Eds.), MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development (pp. 182-195). (MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development; Vol. 2017-January). https://doi.org/10.5220/0006271301820195
Steinberg S, Greenyer J, Gritzner D, Harel D, Katz G, Marron A. Distributing scenario-based models: A replicate-and-project approach. In Pires LF, Hammoudi S, Selic B, editors, MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development. 2017. p. 182-195. (MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development). doi: 10.5220/0006271301820195
Steinberg, Shlomi ; Greenyer, Joel ; Gritzner, Daniel et al. / Distributing scenario-based models : A replicate-and-project approach. MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development. editor / Luis Ferreira Pires ; Slimane Hammoudi ; Bran Selic. 2017. pp. 182-195 (MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development).
Download
@inproceedings{e9dd97b9711942ca8abb2fd8f6b06226,
title = "Distributing scenario-based models: A replicate-and-project approach",
abstract = "In recent years, scenario-based modeling has been proposed to help mitigate some of the underlying difficulties in modeling complex reactive systems, by allowing modelers to specify system behavior in a way that is intuitive and directly executable. This modeling approach simplifies the specification of systems that include events occurring in distinct system components. However, when these system components are physically distributed, executing the scenario-based model requires inter-component coordination that may negatively affect system performance or robustness. We describe a technique that aims to reduce the amount of joint eventselection decisions that require coordination and synchronization among distributed system components. The technique calls for replicating the entire scenario-based executable specification in each of the components, and then transforming it in a component-specific manner that induces the required differences in execution while reducing synchronization requirements. In addition to advantages in streamlining design and improving performance, our approach captures the fact that in certain {"}smart{"} distributed systems it is often required that components know what rules govern the behavior of other components. Our evaluation of the technique shows promising results.",
keywords = "Concurrency, Distributed systems, Scenario-based modeling, Software engineering",
author = "Shlomi Steinberg and Joel Greenyer and Daniel Gritzner and David Harel and Guy Katz and Assaf Marron",
year = "2017",
doi = "10.5220/0006271301820195",
language = "English",
series = "MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development",
pages = "182--195",
editor = "Pires, {Luis Ferreira} and Slimane Hammoudi and Bran Selic",
booktitle = "MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development",
note = "5th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2017 ; Conference date: 19-02-2017 Through 21-02-2017",

}

Download

TY - GEN

T1 - Distributing scenario-based models

T2 - 5th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2017

AU - Steinberg, Shlomi

AU - Greenyer, Joel

AU - Gritzner, Daniel

AU - Harel, David

AU - Katz, Guy

AU - Marron, Assaf

PY - 2017

Y1 - 2017

N2 - In recent years, scenario-based modeling has been proposed to help mitigate some of the underlying difficulties in modeling complex reactive systems, by allowing modelers to specify system behavior in a way that is intuitive and directly executable. This modeling approach simplifies the specification of systems that include events occurring in distinct system components. However, when these system components are physically distributed, executing the scenario-based model requires inter-component coordination that may negatively affect system performance or robustness. We describe a technique that aims to reduce the amount of joint eventselection decisions that require coordination and synchronization among distributed system components. The technique calls for replicating the entire scenario-based executable specification in each of the components, and then transforming it in a component-specific manner that induces the required differences in execution while reducing synchronization requirements. In addition to advantages in streamlining design and improving performance, our approach captures the fact that in certain "smart" distributed systems it is often required that components know what rules govern the behavior of other components. Our evaluation of the technique shows promising results.

AB - In recent years, scenario-based modeling has been proposed to help mitigate some of the underlying difficulties in modeling complex reactive systems, by allowing modelers to specify system behavior in a way that is intuitive and directly executable. This modeling approach simplifies the specification of systems that include events occurring in distinct system components. However, when these system components are physically distributed, executing the scenario-based model requires inter-component coordination that may negatively affect system performance or robustness. We describe a technique that aims to reduce the amount of joint eventselection decisions that require coordination and synchronization among distributed system components. The technique calls for replicating the entire scenario-based executable specification in each of the components, and then transforming it in a component-specific manner that induces the required differences in execution while reducing synchronization requirements. In addition to advantages in streamlining design and improving performance, our approach captures the fact that in certain "smart" distributed systems it is often required that components know what rules govern the behavior of other components. Our evaluation of the technique shows promising results.

KW - Concurrency

KW - Distributed systems

KW - Scenario-based modeling

KW - Software engineering

UR - http://www.scopus.com/inward/record.url?scp=85030776437&partnerID=8YFLogxK

U2 - 10.5220/0006271301820195

DO - 10.5220/0006271301820195

M3 - Conference contribution

AN - SCOPUS:85030776437

T3 - MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development

SP - 182

EP - 195

BT - MODELSWARD 2017 - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development

A2 - Pires, Luis Ferreira

A2 - Hammoudi, Slimane

A2 - Selic, Bran

Y2 - 19 February 2017 through 21 February 2017

ER -