From Integrated Architecture to Integrated Executable Architecture

Helle, Philipp; Levier, Pascal

doi:10.1109/wetice.2010.29

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…19 For example, some have applied discrete-event simulations, 19 while others have combined the ideas of Colored Petri Nets with discrete-event simulation 20 , or performed agent-based simulations. 18 Helle and Levier 21 published a method of converting a traditional integrated architecture into an executable architecture.…”

Section: Introductionmentioning

confidence: 99%

A method of assessing the time-variant value of multi-domain architectures

Ford

Meyer

Colombi

et al. 2016

Journal of Defense Modeling & Simulation

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Modeling and simulation continues to improve the ability to evaluate future complex concepts and conduct early systems analysis. While the systems engineering community now advocates model-based systems engineering, the actual integrated methods and tools need to be refined. This research synthesizes descriptive architectural depictions of multidomain (air and space) concepts, simulates these concepts through a physics-based model, collects several performance metrics, and integrates them using value-focused thinking. The proposed method enables the assessment of alternatives whose value can increase or decrease over time, depending on the design properties and operational scenario. Three surveillance concepts are proposed, made up of a low-earth orbit satellite constellation, with varying payloads, and extended by an unmanned air system flying waypoints in the area of interest. Uniquely, this method shows promise of depicting time-variant value assessments of these concepts across the simulation.

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Section: Introductionmentioning

confidence: 99%

A method of assessing the time-variant value of multi-domain architectures

Ford

Meyer

Colombi

et al. 2016

Journal of Defense Modeling & Simulation

View full text Add to dashboard Cite

show abstract

“…To measure and analyze such dynamic properties on EA models, special kinds of analysis techniques have to be used. Among those, simulation approaches provide advantages such as: (1) comparison of architecture alternatives based on dynamic properties; 6 (2) easy identification of architecture operation defects; 7 (3) architecture components’ roles are easily observed; 7 and (4) architectures can be studied at a high level of detail without a lot of effort. 1 By means of simulation it is also possible to study the influence of the environment over the enterprise, and measure its effect on key indicators about static and dynamic properties; to run experiments to answer what-if questions; and to understand how alternate designs would perform under different scenarios.…”

Section: Introductionmentioning

confidence: 99%

xArchiMate: Enterprise Architecture simulation, experimentation and analysis

et al. 2015

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ArchiMate has recently become the standard language for describing and visualizing Enterprise Architecture models encompassing different domains, their relations, and their dependencies. A few approaches have been proposed for the analysis of ArchiMate models, but they are static and thus focus on structural and static features, leaving aside the analysis of dynamic features. To address this shortfall we propose xArchiMate. It is a model-based approach for executing ArchiMate models and collecting data about dynamic features which is then used, together with static information, to assemble indicators and support decision-making processes. The core of xArchiMate is an execution engine that executes models that conform to the xArchiMate meta-model, which differentiates from the standard ArchiMate meta-model in a few key aspects: it includes behavioral information (e.g. states and interactions) on top of the normal structural information; it includes additional elements that complement and specialize ArchiMate’s base elements; and it only includes elements that have a meaningful behavior and thus are interesting to be simulated. This paper presents xArchiMate, including the meta-model, the execution platform, and a suggested process for creating scenarios and indicators, and then for designing and running experiments to back up decision-making processes on the enterprise.

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“…However, architecture is inherently multidimensional and must be optimized by using a comprehensive and dynamic method, guided by various optimal goals. Therefore, determining an optimal solution or methodology in the architecture design remains a significant challenge [5].…”

Section: Introductionmentioning

confidence: 99%

System deployment optimization in architecture design

Zhang

Shu

Luo

et al. 2014

J. of Syst. Eng. Electron.

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Optimization of architecture design has recently drawn research interest. System deployment optimization (SDO) refers to the process of optimizing systems that are being deployed to activities. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal solutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are minimized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm (HGA), as well as the combination of heuristic method and particle swarm optimization (HPSO). Experiment results show that the HPSO method generates solutions faster than particle swarm optimization (PSO) and genetic algorithm (GA) in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.

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From Integrated Architecture to Integrated Executable Architecture

Cited by 7 publications

References 5 publications

A method of assessing the time-variant value of multi-domain architectures

A method of assessing the time-variant value of multi-domain architectures

xArchiMate: Enterprise Architecture simulation, experimentation and analysis

System deployment optimization in architecture design

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