A Simulation Environment for Intelligent Machine Architectures

Zeigler, Bernard P.; Louri, Ahmed

doi:10.1006/jpdc.1993.1046

Cited by 9 publications

(4 citation statements)

References 13 publications

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“…The characteristics of variable structure demonstrated by the architecture enable the system to manage computing resources efficiently. Since we decoupled the decision-makers from parameter evaluators, the framework is also well-adapted to the intelligent machine architecture [8], which utilizes the high performance distributed/parallel computing power.…”

Section: Discussionmentioning

confidence: 99%

“…An intelligent machine architecture (IMA) was proposed to solve real world problems that contain high degree of complexity and heterogeneity [8]. The architecture should be able to execute symbolic processing as well as numerical computation, of which the processing characteristics differ fundamentally from conventional numerical processors.…”

Section: Brief Review Of Intelligent Machine Architecturementioning

confidence: 99%

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A Framework for Multiresolution Optimization in a Parallel/Distributed Environment: Simulation of Hierarchical GAs

Kim

Zeigler

1996

Journal of Parallel and Distributed Computing

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Section: Discussionmentioning

confidence: 99%

Section: Brief Review Of Intelligent Machine Architecturementioning

confidence: 99%

A Framework for Multiresolution Optimization in a Parallel/Distributed Environment: Simulation of Hierarchical GAs

Kim

Zeigler

1996

Journal of Parallel and Distributed Computing

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“…It provides a natural and effective way to model those complex systems that exhibit structure and behavior changes to adapt to different situations. Examples of these systems include distributed computing systems, reconfigurable computer architectures [30,31], fault tolerant 1) computers [32], and ecological systems [33]. Structure changing and component upgrading is an essential part of these systems.…”

Section: Variable Structure Devsmentioning

confidence: 99%

DEVS-Based Dynamic Model Reconfiguration and Simulation Control in the Enhanced DoDAF Design Process

Mittal

Mak

Nutaro

2006

Journal of Defense Modeling & Simulation

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The combination of DoDAF operational views, which capture the requirements of an architecture, and System views, which provide its technical attributes, forms the basis for semi-automated construction of simulation models. In this paper, we describe an enhanced Model-View-Controller paradigm that works in tandem with the DEVS M&S framework. We also employ the recently introduced DoDAF extensions that incorporate new operational views to allow DoDAF specifications to be written in the Discrete Event System Specification (DEVS) formalism and, in the process, refine these new extensions. This paper describes a DEVS-based network modeling and simulation environment with dynamic reconfiguration and simulation control. The DEVS modeling and simulation framework with its separation of model, experimental frame, and simulator facilitates the development of a simulation framework supporting run-time simulation tuning. We present a layered simulation architecture that provides the capability to control and reconfigure simulation on-the-fly and steer it toward the desired performance parameters. The rapid feedback cycle supported by “real-time” intervention allows experimentation with parameters and structures and results in effective model configuration that is difficult to achieve when turnaround requires hours or days. We explore the area of system reconfiguration further by providing enhanced capabilities to control the parameters for system design and performance evaluation with respect to Net-Ready Key Performance Parameters (NR-KPP) and the way in which the refined DoDAF extensions can expedite the development of Key Interface Profile (KIP) for any DoDAF architecture. We demonstrate the enhanced capabilities with an example of the development of a simulation environment for the Systems Capable of Planned Expansion (SCOPE) command.

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“…Examples of these systems include distributed computing systems, reconfiguration computer architectures [19,20], fault-tolerance computers [21], and ecological systems [15]. Structure changing and component upgrading is an essential part of these systems.…”

Section: Conceptual Development For Variable Structure In Devsmentioning

confidence: 99%

Variable Structure in DEVS Component-Based Modeling and Simulation

Zeigler

Mittal

2005

SIMULATION

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Variable structure refers to the ability of a system to dynamically change its structure according to different situations. It provides component-based modeling and simulation environments with powerful modeling capability and the flexibility to design and analyze complex systems. In this article, the authors discuss variable structure—specifically, the structure change and interface change capability—in DEVS-based modeling and simulation environments. The operations of structure change and interface change are discussed, and their respective operation boundaries are defined. Three examples are given to illustrate the role of variable structure and how it can be used to model and design adaptive complex systems. Principles for the implementation of variable structure are also presented and illustrated in the DEVSJAVA modeling and simulation environment.

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A Simulation Environment for Intelligent Machine Architectures

Cited by 9 publications

References 13 publications

A Framework for Multiresolution Optimization in a Parallel/Distributed Environment: Simulation of Hierarchical GAs

A Framework for Multiresolution Optimization in a Parallel/Distributed Environment: Simulation of Hierarchical GAs

DEVS-Based Dynamic Model Reconfiguration and Simulation Control in the Enhanced DoDAF Design Process

Variable Structure in DEVS Component-Based Modeling and Simulation

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