This article presents a framework for distributed simulation that is based on system-theoretic and logical-process concepts. The framework describes a three-part worldview for developing simulation models. These are modeling formalisms, abstract simulators, and computational environments. A unified view of time and causality allows for the application of system-theoretic notions of causality within a distributed simulation environment. Within this framework, the authors introduce a unified notion of causality for use in parallel simulations. Furthermore, they describe an approach for developing distributed simulation models that evolve from modeling constructs to simulation algorithms and their implementations. The framework is exemplified using the discrete event system specification (DEVS) modeling formalism, its abstract simulator, and a parallel algorithm that implements the abstract simulator.
Garg, V. K.1996. Principles of distributed systems. Boston: Kluwer Academic .
2.
Tel, G.2000. Introduction to distributed algorithms. Cambridge, UK: Cambridge University Press .
3.
Fujimoto, R. M.2000. Parallel and distributed simulation systems. New York: John Wiley .
4.
Zeigler, B. P. , G. Ball , H. Cho , J. S. Lee , and H. Sarjoughian . 1999. Implementation of the DEVS formalism over the HLA/RTI: Problems and solutions . Paper presented at the Simulation Interoperability Workshop, March, Orlando, FL.
5.
Zeigler, B. P. , H. Praehofer , and T. G. Kim . 2000. Theory of modeling and simulation. 2nd ed.San Diego: Academic Press .
6.
Bagrodia, R. , K. M. Chandy , and Wen Toh Liao . 1991. A unifying framework for distributed simulation . ACM Transactions on Modeling and Computer Simulation1 (4): 348-385 .
7.
Fujimoto, R. M.1998. Parallel and distributed simulation. In Handbook of simulation, edited by Jerry Banks . New York: John Wiley .
8.
Mesarovic, M. D. , and Y. Takahara . 1989. Abstract systems theory. Berlin: Springer-Verlag .
Rönngren, R. , and M. Liljenstam . 1999. On event ordering in parallel discrete event simulation . In Thirteenth Workshop on Parallel and Distributed Simulation, pp. 38-45 .
11.
Lamport, L.1978. Time, clocks and the ordering of events in a distributed system . Communications of the ACM21 (7): 558-565 .
12.
Nutaro, J. J. 2000. Time management and interoperability in distributed discrete event simulation. Master’s thesis, University of Arizona, Department Electrical and Computer Engineering.
13.
Zeigler, B. P.1976. Theory of modeling and simulation. New York: John Wiley .
14.
Kofman, E.2003. Quantization-based simulation of differential algebraic equation systems. Technical Report LSD0203, LSD, Universidad Nacional de Rosario .
15.
Wieland, F.1999. The threshold of event simultaneity . Transactions of the Society for Computer Simulation International16 (1): 23-31 .
16.
Nicol, D. , J. Liu , and J. Cowie . 2000. Safe timestamps and large-scale modeling . In Proceedings of the 14th Workshop on Parallel and Distributed Simulation, May, Bologna, Italy, pp. 71-78 .
17.
Barz, C. , Rolf Göpffarth , P. Martini , and A.e Wenzel . 2003. A new framework for the analysis of simultaneous events . In Proceedings of SCSC’03 (Summer Computer Simulation Conference), July, Montreal, Canada.
18.
Jha, V. , and R. Bagrodia . 2000. Simultaneous events and lookahead in simulation protocols . ACM Transactions on Modeling and Computer Simulation10 (3): 241-267 .
19.
Frey, P. , R. Radhakrishnan , H. W. Carter , Philip A. Wilsey , and P. Alexander . 2002. A formal specification and verification framework for time warp-based parallel simulation . IEEE Transactions on Software Engineering28 (1): 58-78 .
20.
Ghosh, S.1996. On the proof of correctness of yet another asynchronous distributed discrete event simulation algorithm (YADDES) . IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans26 (1): 68-80 .
21.
Sarjoughian, H. S. , and B. P. Zeigler . 2000. DEVS and HLA: Complementary paradigms for M&S?Transactions of the Society for Computer Simulation17 (4): 187-197 .
22.
Ferscha, A.1995. Parallel and distributed simulation of discrete event systems. In Handbook of parallel and distributed computing, edited by A. Y. Zomaya . New York: McGraw-Hill .
23.
Mattern, F.1994. Detecting causal relationships in distributed computations: In search of the Holy Grail . Distributed Computing7 (3): 149-174 .
24.
Nutaro, J.J. and H.S. Sarjoughian . 2001. Speedup of a sparse system simulation . In 15th Workshop on Parallel and Distributed Simulation, May, Lake Arrowhead, CA, pp. 193-199 .
25.
Nutaro, J. J. 2003. Parallel discrete event simulation with application to continuous systems. Ph.D. diss., University of Arizona, Department of Electrical and Computer Engineering.
26.
Chow, A. C.-H.1996. Parallel DEVS: A parallel, hierarchical, modular modelling formalism and its distributed simulation . Transactions of the Society for Computer Simulation International, 13 (2): 55-67 .
27.
Bass, L. , P. Clements , and R. Kazman . 1997. Software architecture in practice. Reading, MA: Addison-Wesley .
28.
Sarjoughian, H. S. , B. P. Zeigler , and S. B. Hall . 2001. A layered modeling and simulation architecture for agent-based system development . IEEE Proceedings89 (2): 201-213 .
29.
Steinman, J. S.1992. SPEEDES: A multiple-synchronization environment for parallel discrete event simulation . International Journal for Computer Simulation2 (3): 251-286 .
30.
Barros, F. J.1998. Handling simultaneous events in dynamic structure models . SPIE Proceedings: Enabling Methodologies for Simulation3369: 355-363 .
31.
Snir, M. , S. Otto , S. Huss-Lederman , D. Walker , and J. Dongarra . 1998. MPI—The complete reference:Vol. 1. The MPI core. 2nd ed.Cambridge, MA: MIT Press .
