Skip to main content
Log in

Scalability and Performance Evaluation of DDM-Based Aggregation/Dissaggregation Protocols for Large-Scale Distributed Interactive Simulations Systems

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Aggregation/disaggregation is a method for implementing multi-resolution simulations within a High Level Architecture (HLA) federation. HLA is a U.S. Department of Defense (DoD) developed standard to facilitate linking different types of simulations, in various locations, to form an or interactive, full-scale simulation, called a federation. Data Distribution Management (DDM) is a High Level Architecture/Run-time Infrastructure (HLA/RTI) service that manages the distribution of state updates and interaction information and controls the volume of data exchanged, in large-scale distributed simulations. The purpose of HLA is to promote interoperability and reuse among heterogenous simulations, including those simulations that offer varied levels of resolution, to provide practical training to military personnel of different ranks. The purpose of Aggregation/disaggregation is to ensure consistency in state updates between federates simulating objects at various levels of resolution. This paper focuses on the scalability of aggregation/disaggregation with different DDM implementations and examines the effects, on performance of large-scale simulations. We implement a federate-based aggregation/disaggregation scheme, originally introduced in [TAN01], with a tank dogfight scenario, aggregating five tanks into one tank battalion and disaggregating the battalion back into five individual entities (tanks). The DDM methods we analyze consist of the Fixed Grid-Based method, the Dynamic Grid-Based method and the Region-Based method. In [TAN01], testing of this federate-based aggregation/disaggregation was limited to a dual federation and a single DDM scheme. In an effort to determine the scalability of aggregation/disaggregation, with three methods of DDM, we measure the communication overhead and analyze performance during a federation execution. We present the results of extensive testing, varying the number of aggregation/disaggregation requests, the number of multi-resolution federates participating in the federation, the number of objects, the number/size of the grids and report on the performance evlauation of our protocols using an extensive set of simulation experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. A. Berrached. Alternative Approaches to Multicast Group Allocation in HLA Data Distribution Management, Spring SIW Workshop, 1998.

  2. A. Boukerche and C. Dzermajko. Performance comparison of data distribution management strategies, in Proceedings Fifth IEEE International Workshop on Distributed Simulation and Real-Time Applications, 2001, pp. 67–75.

  3. A. Boukerche and A. J. Roy. In search of DDM in large-scale distributed simulations, Summer Simulation Conference, 12–19, 2000.

  4. A. Boukerche and A. J. Roy. Dynamic grid-based multicast group assignment in data distribution management, in Proceedings Fourth IEEE International Workshop on Distributed Simulation and Real-Time Applications, 27–34, 2000.

  5. A. Boukerche and A. J. Roy. Dynamic grid-based approach to data distribution management, Journal of Parallel and Distributed Computing, 62, 366–392, 2002.

    Google Scholar 

  6. A. Boukerche, C. Dzermajko, and R. Aurajo. “Performance evaluation of data distribution management strategies,“ Technical Report, University of Ottawa—In preparation.

  7. A. Boukerche. “Time management in parallel simulation,“High Performance Cluster Computing, Prentice Hall, Vol. 2, Ed. B. Rajkumar, pp. 375–394, 1999.

  8. J. O. Calvin, C. J. Chiang, S. M. McGarry, S. J. Rak, and D. J. Van Hook. Design, implementation, and performance of the STOW RTI prototype (RTI-s), 99S-SIW-019, Spring SIW Workshop, 1999.

  9. J. S. Dahmann and K. L. Morse. High level architecture for simulation: An update, in Proceedings Third IEEE International Workshop on Distributed Simulation and Real-Time Applications, 1998, pp. 32–40.

  10. R. T. Fujimoto. Parallel and distributed simulation systems, John Wiley and Sons, New York, 2000.

    Google Scholar 

  11. R. T. Fujimoto, T. Mclean, K. Perumalla, and I. Tacic. Design of high performance RTI software, in Proceedings Fourth IEEE International Workshop on Distributed Simulation and Real-Time Applications, 2000, pp. 41–49.

  12. R. T. Fujimoto and I. Tacic. Synchronized data distribution management in distributed simulations, in Proceedings Twelfth Workshop on Parallel and Distributed Simulation, 1998.

  13. George Mason University Center of Excellence in Command, Control, Communications, and Intelligence, Selectively Reliable Transport Protocol, http://bacon.gmu.edu/c3i/index.html, 2000.

  14. P. Huang, D. Estrin, and J. Heidemann. Enabling Large-scale simulations: Selective abstraction approach to the study of multicast protocols, in Proceedings Sixth IEEE/ACM International Workshop on Modeling, Analasis and Simulation of Computer and Telecommunication Systems, 1998, pp. 241–248.

  15. G. Koldag and V. Isler. Multiresolution behavioral modeling in a virtual environment, Thirty-Third Annual Simulation Symposium, 2000, pp. 192–197.

  16. K. L. Morse, M. Petty. Data distribution management migration from DoD 1.3 to IEEE 1576, in Proceedings Fifth IEEE International Workshop on Distributed Simulation and Real-Time Applications, 2001, pp. 58–65.

  17. K. L. Morse and J. S. Steinman. “Data distribution management in the hla: multidimensional regions and physically correct filtering,“ in Proceedings Spring SIW Workshop, 1997, 97S-SIW-052.

  18. A. Natrajan, P. F. Reynolds, Jr., and S. Srinivasan. MRE: A flexible approach to multi-resolution modeling, in Proceedings Eleventh Workshop on Parallel and Distributed Simulation, 1997, pp. 156–163.

  19. M. J. Pullen, V. P. Laviano, and M. Moreau. Creating a light-weight rti using selectively reliable transmission as an evolution of dual-mode multicast, in Proceedings Fall SIW Workshop, 1997, 97F-SIW-149.

  20. R. Radhakrishnan and P. A. Wilsey. Ruminations on the implications of multi-resolution modeling on DIS/HLA, in Proceedings Third IEEE International Workshop on Distributed Simulation and Real-Time Applications, 1999, pp. 101–108.

  21. S. J. Rak. Evaluation of grid based relevance filtering for multicast group assignment, in Proceedings Fourteenth DIS/SIW Workshop, 1996, 96–14–106.

  22. D. M. Rao and P. A. Wilsey. Multi-resolution network simulations using dynamic component substitution, in Proceedings Ninth IEEE/ACM International Workshop on Modeling, Analasis and Simulation of Computer and Telecommunication Systems, 2001, pp. 142–149.

  23. P. F. Reynolds, Jr. and S. Srinivasan. Communications, data distribution and other goodies in the hla performance model, in Proceedings Spring SIW Workshop, 1997, 97S-SIW-050.

  24. A. J. Roy. Dynamic grid-based data distribution management in large scale distributed simulations, Master of Science Thesis, University of North Texas, 2000.

  25. J. S. Steinman and F. Wieland. Parallel proximity detection and the distribution list algorithm, in Proceedings Eighth Parallel and Distributed Simulation Workshop, 1994, pp. 3–11.

  26. G. Tan, L. Xu, F. Moradi, and Y. Zhang. An agent-based DDM filtering mechanism, in Proceedings Eighth IEEE/ACM International Workshop on Modeling, Analasis and Simulation of Computer and Telecommunication Systems, 2000, pp. 374–381.

  27. G. Tan, W. N. Ng, and F. Moradi. Aggregation/disaggregation in HLA multi-resolution distributed simulation, in Proceedings Fifth IEEE International Workshop on Distributed Simulation and Real-Time Applications, 2001, pp. 76–83.

  28. G. Tan, Y. Zhang, and R. Ayani. Grid-based data management in distributed simulation, in Proceedings Thirty-third Annual Simulation Symposium, 2000, pp. 7–13.

  29. U. S. Department of Defense, Defense Modeling and Simulation Office, High level architecture interface specification, April 2, 1998, http://www.dmso.mil/public/resources/documents, link to: Project Areas, High Level Architecture, Technical Specifications.

  30. D. J. Van Hook, S. J. Rak, and James O. Calvin. Approaches to RTI implementation of HLA data distribution management services, 15th DIS, 1996.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Azzedine Boukerche.

Additional information

This work was partially supported by Grants from NSERC, Canada Research Chairs Program, Canada Foundation for Innovation, OIT/Distinguished Researcher Award.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Boukerche, A., Dzermajko, C. Scalability and Performance Evaluation of DDM-Based Aggregation/Dissaggregation Protocols for Large-Scale Distributed Interactive Simulations Systems. J Supercomput 35, 259–276 (2006). https://doi.org/10.1007/s11227-006-4669-6

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-006-4669-6

Keywords

Navigation