Generalized Discrete Event Simulation of Bond GraphNaamane, A.; Giambiasi, N.; Damiba, A.
doi: 10.1177/003754970107700101pmid: N/A
We propose a new approach dealing with the com bination of bond-graph with GDEVS formalism for modeling and simulation of complex systems using discrete event techniques. We show how to build discrete event simulation models for bond graph elements, with either piecewise linear in put-output trajectories or any kind of polynomial trajectories. One of the main advantages of our method is the reduction in the number of simula tion steps, and therefore the possibility of study ing dynamic hybrid systems using only the dis crete event paradigm.
Simulation-based SW/HW Architectural Design Configurations for Distributed Mission Training SystemsSarjoughian, Hessam S.; Hild, Daryl R.; Xiaolin Hu, ; Strini, Robert A.
doi: 10.1177/003754970107700102pmid: N/A
Distributed Mission Training (DMT) is a concept composed of promising technologies that support training in a variety of domains such as defense and medicine. To develop and deploy such systems, it is important to account concurrently for hardware and software requirements, given high demands for net work bandwidth, computing resources, and com plexity of software applications. In this paper, we present the application of a distributed co-design methodology (Discrete Event System Specification/ Distributed Object Computing) as applied to the Mission Training and Rehearsal System (MTRS), a DMT system. For an example, we show that the developed simulation models allow prediction of the network capacity below which messages cannot be sent and therefore incorrect behavior results. The key issues presented are (1) characterization of the DMT style architectures in DEVS/DOC, (2) prediction of DMT-like basic scalability traits via simulation, and (3) discussion on some open problems underlying the applicability of distributed co-design for systems containing "off-the-shelf' components.
Design and Development of Data Distribution Management EnvironmentLee, Jong S.; Zeigler, Bernard P.; Venkatesan, Shankar M.
doi: 10.1177/003754970107700103pmid: N/A
This paper describes the design and development of the DEVS/GDDM environment, a layered simulation environment that supports data dis tribution management and allows us to study space-based quantization schemes. These schemes aim to achieve effective reduction of data commu nication in distributed simulation. After a brief review of the space-based quantization scheme and an HLA-Interface environment, we discuss the design issues of the DEVS/GDDM environ ment. We analyze system performance and scalability of the space-based quantization scheme, especially with predictive and multiplex ing extensions, and empirical results for a ballis tic missiles simulation executing on the DEVS/ GDDM environment on NT networking plat forms. The results indicate the DEVS/GDDM environment is very effective and scalable due to reduced local computation demands and ex tremely favorable communication data reduction.
Modeling Forest Landscapes: Parameter Estimation from Gap Models over Heterogeneous TerrainAcevedo, Miguel F.; Pamarti, Siva; Ablan, Magdiel; Urban, Dean L.; Mikler, Armin
doi: 10.1177/003754970107700104pmid: N/A
Parameter values of a forest landscape model (MO SAIC) are estimated from a terrain sensitive gap model (FACET) over a large number of terrain types. MOSAIC is a semi-Markov model with states defined by cover types. For each terrain type, gap-model output is fed to a program that counts transitions between each pair of states, and estimates the fixed lags and the parameters of the probability density functions of the distributed delays. The gap model and the parameter estimator are executed repetitively for many different steps in the gradients and many ter rain types, taking advantage of a computer cluster running a distributed launching system. The method is illustrated by its application to the H.J. Andrews Forest in the Oregon Cascades. Key transitions in cover type determine the variation of the landscape- model parameters over all terrain types. The method ology presented here provides an automated, consis tent and conceptually clear procedure for scaling up the tree level ecological detail represented by a gap model, to the level ofa patch state-transition model for heterogeneous environmental conditions across the landscape.