4,309 research outputs found
Higher Level Modeling in RESQME
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
An Introduction to the RESearch Queueing Package for Modeling Computer Systems and Communication Networks
A queueing network is an important tool for modeling systems where performance is principally affected by contention for resources. Such systems include computer systems, communication networks and manufacturing lines. In order to effectively use queuing networks as performance models, appropriate software is necessary for definition ofthe networks to be solved, for solution ofthe networks and for examination of the performance measures obtained. The RESearch Queueing Package (RESQ) and the RESearch Queueing Package Modeling Environment (RESQME) form a system for constructing, solving and analyzing extended queueing network models. We refer to the class of RESQ networks as extended because of characteristics which allow effective representation of system detail. RESQ incorporates a high level language to concisely describe the structure of the model and to specify constraints on the solution. A main feature of the language is the capability to describe models in a hierarchical fashion, allowing an analyst to define submodels to be used analogously to use of macros in programming languages. RESQ also provides a variety of methods for estimating the accuracy of simulation results and for determining simulation run lengths. RESQME is a graphical interface for RESQ. In this introduction, we limit our examples to computer systems and communication networks.
Acknowledgement: The authors wish to thank their co-developers of RESQME: Jim Kurose and Kurt Gordon. We also want to thank Ben Antanaitis, Howard Jachter, Jack Servier, Daniel Souday and Peter Welch for their many suggestions which helped improve the RESQME package and Anil Aggarwal, Al Blum, Gary Burkland, Rocky Chang, Janet Chen, Diana Coles, Prakash Deka, Paul Lnewner, and Geoff Parker for their work in implementing RESQME. We would also like to thank our users for their ideas and feedback that we tried to incorporate in RESQ and RESQME. We remain indebted to Charlie Sauer for his design, guidance, inspiration, and development ofthe RESQ languag
RESQME and Stand-Alone Simulation on a Workstation
RC 16037 (#71232)
The Research Queueing Package Modeling Environment (RESQME) provides a graphical environment for constructing and solving extended queueing network models ofmanufacturing systems, for plotting graphs of results and for viewdng animations of models. The modeling environment can be run entirely on a workstation or optionally can execute large simulations on a host system using cooperative processing. In this paper we give a brief introduction to RESQME and to the RESQ modeling elements. We demonstrate how to use the package by constructing a simple model of part of a manufacturing line and solve this model to produce charts of performance measures and an animation which shows how the jobs flow through the system. By having the simulation available for use on the workstation and cooperatively on the host, RESQME provides a unique tool for understanding the performance of manufacturing systems. A user can do most of the model debugging locally on the workstation and make short püot runs to get a feeling for the amount of resources necessary to make more realistic experiments on the • host. Then long runs which investigate large parts ofthe parameter space can be done cooperatively on the host. Whether the model is solved on the workstation or on the hosMhe graphics environment provides the same user interface to all of the underlying files. The processor where the model is solved is transparent to the user. In aU cases, the user has easy access to plots ofresults and to the animation ofthe model diagra
Computationally Efficient Simulation of Queues: The R Package queuecomputer
Large networks of queueing systems model important real-world systems such as
MapReduce clusters, web-servers, hospitals, call centers and airport passenger
terminals. To model such systems accurately, we must infer queueing parameters
from data. Unfortunately, for many queueing networks there is no clear way to
proceed with parameter inference from data. Approximate Bayesian computation
could offer a straightforward way to infer parameters for such networks if we
could simulate data quickly enough.
We present a computationally efficient method for simulating from a very
general set of queueing networks with the R package queuecomputer. Remarkable
speedups of more than 2 orders of magnitude are observed relative to the
popular DES packages simmer and simpy. We replicate output from these packages
to validate the package.
The package is modular and integrates well with the popular R package dplyr.
Complex queueing networks with tandem, parallel and fork/join topologies can
easily be built with these two packages together. We show how to use this
package with two examples: a call center and an airport terminal.Comment: Updated for queuecomputer_0.8.
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Modeling and simulation of data communication networks using SARA
The selection of an appropriate simulation language can have a profound impact on the success of a simulation study. The available options range from domain-specific simulation languages to general-purpose programming languages. These languages are often supported by a collection of tools which form a simulation system. This paper examines UCLA's SARA (Systems ARchitects' Apprentice) system and explores its' usefulness in modeling and simulating a data communications network. Based on experimental use of SARA's tools, the system is evaluated with respect to required expertise, modeling power, as well as measurement and reporting capability
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