Heterogeneous DEVS simulations with connectors and reo based compositions [Work in Progress]

Date

2014-01-01

Author

Kara, Ahmet
Oğuztüzün, Mehmet Halit S.
Nedim Alpdemir, M.

Metadata

Show full item record

Item Usage Stats

71
views

0
downloads

Composition of DEVS models in heterogenous environments requires resolutions for manifold incompatibilities including data type and time resolution mismatch. This paper proposes a solution for implementing DEVS simulations in heterogenous environments with the help of connectors in the sense of component based software engineering. Our solution involves implementing connectors as atomic models to be used in mediation of data type and time resolution mismatches. Employing atomic models as connectors allows connector composition in the style of Reo and promotes higher level of reuse in simulation construction. In this paper we describe our solution formally and present a case study to demonstrate its application.

Subject Keywords

Connectors, DEVS, Model composition, Reo

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84902014288&origin=inward
https://hdl.handle.net/11511/73275
https://dl.acm.org/doi/10.5555/2665008.2665009

Conference Name

2014 Symposium on Theory of Modeling and Simulation - DEVS Integrative M and S Symposium, DEVS 2014; 2014 Spring Simulation Multi-Conference, SpringSim 2014 (13 - 16 Nisan 2014)

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Distance-based discretization of parametric signal manifolds Vural, Elif (2010-06-28) The characterization of signals and images in manifolds often lead to efficient dimensionality reduction algorithms based on manifold distance computation for analysis or classification tasks. We propose in this paper a method for the discretization of signal manifolds given in a parametric form. We present an iterative algorithm for the selection of samples on the manifold that permits to minimize the average error in the manifold distance computation. Experimental results with image appearance manifolds d...
Decoupled Modular Regularized VMS-POD for Darcy-Brinkman Equations Güler Eroğlu, Fatma; Kaya Merdan, Songül; Rebholz, Leo G (2019-05-01) We extend the post-processing implementation of a projection based variational multiscale (VMS) method with proper orthogonal decomposition (POD) to flows governed by double diffusive convection. In the method, the stabilization terms are added to momentum equation, heat and mass transfer equations as a completely decoupled separate steps. The theoretical analyses are presented. The results are verified with numerical tests on a benchmark problem.
Curvature analysis of pattern transformation manifolds Vural, Elif (2010-12-03) Transformation manifolds are quite attractive for image analysis applications that require transformation invariance properties. The geometric structure of a transformation manifold has a profound influence on the design of processing algorithm, and the curvature is a major parameter in the characterization of the manifold geometry. We propose here a procedure for the computation of an upper bound for the maximum principal curvature of a pattern transformation manifold. We provide an analytical formulation ...
Convergence acceleration based on convergence error estimation Eyi, Sinan (2013-01-01) New methods are developed for convergence error estimation and convergence acceleration in iteratively solved problems. The convergence error estimation method is based on the eigenvalue analysis of linear systems, but it can also be used for nonlinear systems. Newton's method is used to estimate the magnitude and the phase angle of eigenvalues. The convergence of iterative method is accelerated by subtracting convergence error from the iteratively calculated solutions. The performances of these methods are...
Learning Smooth Pattern Transformation Manifolds Vural, Elif (2013-04-01) Manifold models provide low-dimensional representations that are useful for processing and analyzing data in a transformation-invariant way. In this paper, we study the problem of learning smooth pattern transformation manifolds from image sets that represent observations of geometrically transformed signals. To construct a manifold, we build a representative pattern whose transformations accurately fit various input images. We examine two objectives of the manifold-building problem, namely, approximation a...

Citation Formats

A. Kara, M. H. S. Oğuztüzün, and M. Nedim Alpdemir, “Heterogeneous DEVS simulations with connectors and reo based compositions [Work in Progress],” Tampa, FL, Amerika Birleşik Devletleri, 2014, vol. 46, p. 1, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84902014288&origin=inward.