9 research outputs found

    Higher Level Modeling in RESQME

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    RC 13554 (#60544) The RESearch Queueing Package Modeling Environment (RESQME) is a graphical workstation environment for iteratively constructing, running and analyzing models of resource contention systems. It is built on top of the RESearch Queueing Package (RESQ) which provides the functionality to evaluate extended queueing networks. In this paper we describe the high-level building component design for RESQME. The modeler is provided with tools to create his own icons and to associate them with submodels. He then uses ilicsc building blocks to construct his model. This capability extends the funtlaiiicnlal building blocks of RESQ and allows the user to create models with objccls directly related to his application domain

    Spreadsheet or database: Which makes more sense?

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    A visual progranmming approach to manufacturing modeling

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    The RESearch Queueing Package Modeling Environment (RESQME) is an interactive, graphics-oriented workstation environment for iteratively constructing, running and analyzing models of resource contention systems. It is built on top of the RESearch Queueing Package (RESQ) which provides the functionality to evaluate extended queueing networks. In this paper we describe how to create a “pull” system, a manufacturing line with finite buffers, using the graphical interface and hierarchical modeling capability. This serves as an example of the kind of manufacturing submodels that can be created in this system and then used for higher-level modeling

    An Extensible Visual Environment for Construction and Analysis of Hierarchically-Structured Models of Resource Contention System

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    The development of models for evaluating the performance of resource contention systems, such as manufacturing systems, computer systems, and communication networks, is often a difficult and complex task. This modeling effort can be dramatically reduced by the use of appropriate software tools. The Research Queueing Package Modeling Environment (RESQME) provides a graphical environment for constructing, solving, and analyzing the results of extended queueing network models of resource contention systems. It supports a rich underlying modeling paradigm previously developed in the Research Queueing Package (RESQ) and provides a single integrated graphical interface throughout all tasks of the modeling lifecycle. In this paper we present a brief overview of RESQME and then focus on two of its most important features: the construction and analysis of hierarchically-structured models and the ability to extend and customize the RESQME environment for domain-specific modeling via the use of user-defined modeling elements. A manufacturing model is developed in order to illustrate these capabilities

    Animating Simulations

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    The RESearch Queueing Package Modeling Environment, RESQME, is a graphical environment for creating and modifying queueing models and for evaluating and analyzing the results. An animation facility is a natural adjunct to the graphics-oriented capabilities of this system. In such an environment, animation provides a powerful tool for effectively visualizing massive amounts of information. This makes it easier for the modeler to relate events in the model with processing in the real-world system. Animation enhances the modeler\u27s ability to debug the model, to understand the model interactions and the impact of model changes, and to communicate the results to others. In this paper, we describe the animation facility in RESQME

    Examples of Using the RESearch Queueing Package Modeling Environment

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    The RESearch Queueing Package Modeling Environment (RESQME) is a system which provides an integrated, graphics-oriented, performance evaluation workstation environment for constructing, maintaining, revising and evaluating performance models of resource contention systems. In this paper we discuss examples illustrating its use and emphasize the iterative nature of the modeling process. Scenarios of model specification, selection and use of confidence interval methods, and model output analysis are introduced
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