Analyzing Virtual World Region Fidelity on Scalability and Simulation Performance
Affiliation(s)
1 US Army Research Laboratory, Orlando, FL, USA. 2 Institute for Simulation and Training, University of Central Florida, Orlando, FL, USA.
1 US Army Research Laboratory, Orlando, FL, USA. 2 Institute for Simulation and Training, University of Central Florida, Orlando, FL, USA.
ABSTRACT
Virtual world simulation offers tremendous potential opportunities to improve, and optimize, individual and collective echelon training for the military. The US Army Research Laboratory (ARL) Military Open Simulator Enterprise Strategy (MOSES) project’s charter is to investigate simulation-based training technology for use in military specific training domains. Of particular interest are attributes of virtual worlds such as geographically distributed large-scale trainee support. We have initiated a series of experiments to determine appropriate benchmarks for simulator performance and to determine appropriate independent variables in order to create a robust predictive model that will enable virtual world training scenario designers to calculate, a priori, the number of trainees that may synchronously operate in a virtual world. The present paper’s purposes were to determine the effect that virtual world region fidelity had on server performance and determine whether this independent variable would be appropriate for inclusion into our predictive model. We found that region fidelity had a statistically significant effect on the simulator’s processor memory usage but had no significant effect on the simulator’s vertical scalability, CPU usage nor network performance. In this paper, we discourse on the purpose of this research, our experimental methodology and results, and discuss the significance of our findings.
Virtual world simulation offers tremendous potential opportunities to improve, and optimize, individual and collective echelon training for the military. The US Army Research Laboratory (ARL) Military Open Simulator Enterprise Strategy (MOSES) project’s charter is to investigate simulation-based training technology for use in military specific training domains. Of particular interest are attributes of virtual worlds such as geographically distributed large-scale trainee support. We have initiated a series of experiments to determine appropriate benchmarks for simulator performance and to determine appropriate independent variables in order to create a robust predictive model that will enable virtual world training scenario designers to calculate, a priori, the number of trainees that may synchronously operate in a virtual world. The present paper’s purposes were to determine the effect that virtual world region fidelity had on server performance and determine whether this independent variable would be appropriate for inclusion into our predictive model. We found that region fidelity had a statistically significant effect on the simulator’s processor memory usage but had no significant effect on the simulator’s vertical scalability, CPU usage nor network performance. In this paper, we discourse on the purpose of this research, our experimental methodology and results, and discuss the significance of our findings.
KEYWORDS
Region Fidelity, Vertical Scaling, Virtual World Simulation, Performance Analysis, Distributed Simulation
Region Fidelity, Vertical Scaling, Virtual World Simulation, Performance Analysis, Distributed Simulation
Cite this paper
Mondesire, S. , Stevens, J. , Leis, R. and Maxwell, D. (2015) Analyzing Virtual World Region Fidelity on Scalability and Simulation Performance. Open Journal of Modelling and Simulation, 3, 126-135. doi: 10.4236/ojmsi.2015.33014.
Mondesire, S. , Stevens, J. , Leis, R. and Maxwell, D. (2015) Analyzing Virtual World Region Fidelity on Scalability and Simulation Performance. Open Journal of Modelling and Simulation, 3, 126-135. doi: 10.4236/ojmsi.2015.33014.
References
[1] Lele, A. (2013) Virtual Reality and its Military Utility. Journal of Ambient Intelligence and Humanized Computing, 4, 17-26.
http://dx.doi.org/10.1007/s12652-011-0052-4 [2] Harrington, M. (2011) Empirical Evidence of Priming, Transfer, Reinforcement, and Learning in the Real and Virtual Trillium Trails. IEEE Transactions on Learning Technologies, 4, 175-186.
http://dx.doi.org/10.1109/TLT.2010.20 [3] Blow, C. (2012) Flight School in the Virtual Environment. United States Army Command and General Staff College, Fort Leavenworth, Kansas. [4] Seymour, N., Gallagher, A., Roman, S., O’Brien, M., Bansal, V., Anderson, D. and Satava, R. (2002) Virtual Reality Training Improves Operating Room Performance. Annals of Surgery, 236, 458-464.
http://dx.doi.org/10.1097/00000658-200210000-00008 [5] Hays, R., Jacobs, J., Price, C. and Salas, E. (1992) Flight Simulator Training Effectiveness: A Meta-Analysis. Military Psychology, 4, 63-74.
http://dx.doi.org/10.1207/s15327876mp0402_1 [6] Salas, E., Rosen, M., Held, J. and Weissmuller, J. (2009) Performance Measurement in Simulation-Based Training: A Review and Best Practices. Simulation & Gaming, 40, 328-376.
http://dx.doi.org/10.1177/1046878108326734 [7] Dawley, L. and Dede, C. (2013) Situated Learning in Virtual Worlds and Immersive Simulations. In: Spector, J.M., Merrill, M.D., Elen, J. and Bishop, M.J., Eds., Handbook of Research on Educational Communications and Technology, New York, Springer, 723-734.
http://www.amazon.com/Handbook-Research-Educational-Communications-Technology/dp/1461431840 [8] Dutta, D. (1999) Simulation in Military Training: Recent Developments. Defense Science Journal, 49, 275-285.
http://dx.doi.org/10.14429/dsj.49.3840 [9] Stafford, R.J. and Thornhill, W.M. (2012) The Army Learning Model: Changing the Way Sustainers Train. Army Sustainment, 44, 28-31. [10] Linden Research, Inc. (2015) Second Life Official Site.
http://secondlife.com/ [11] Overte Foundation (2015) Main Page.
http://opensimulator.org/ [12] Mondesire, S.C., Stevens, J. and Maxwell, D.B. (In Press) Vertical Scalability Benchmarking in Three-Dimensional Virtual Worlds Simulation. Proceedings of the 2015 Summer Simulation Multi-Conference, Chicago, 26-29 July 2015. [13] Mondesire, S.C., Stevens, J. and Maxwell, D.B. (In Press) An Analysis of Increases Vertical Scaling in Three-Dimensional Virtual World Simulation. Proceedings of the 8th International Conference on Simulation Tools and Techniques, Athens, 24-26 August 2004. [14] Mondesire, S.C., Stevens, J. and Maxwell, D.B. (Submitted) Network Bandwidth’s Effect on Virtual World Simulator Performance Optimization. Proceedings of the 2015 Interservice/Industry Training, Simulation and Education Conference (I/ITSEC), Orlando, 30 November-4 December 2015. [15] Stevens, J., Mondesire, S.C., and Maxwell, D.B. (Submitted) Human Entities’ Effect on Server Performance in Distributed Virtual World Training. Proceedings of the 2015 Fall Simulation Interoperability Workshop, Orlando, 30 August-4 September 2015.
[1] Lele, A. (2013) Virtual Reality and its Military Utility. Journal of Ambient Intelligence and Humanized Computing, 4, 17-26.
http://dx.doi.org/10.1007/s12652-011-0052-4 [2] Harrington, M. (2011) Empirical Evidence of Priming, Transfer, Reinforcement, and Learning in the Real and Virtual Trillium Trails. IEEE Transactions on Learning Technologies, 4, 175-186.
http://dx.doi.org/10.1109/TLT.2010.20 [3] Blow, C. (2012) Flight School in the Virtual Environment. United States Army Command and General Staff College, Fort Leavenworth, Kansas. [4] Seymour, N., Gallagher, A., Roman, S., O’Brien, M., Bansal, V., Anderson, D. and Satava, R. (2002) Virtual Reality Training Improves Operating Room Performance. Annals of Surgery, 236, 458-464.
http://dx.doi.org/10.1097/00000658-200210000-00008 [5] Hays, R., Jacobs, J., Price, C. and Salas, E. (1992) Flight Simulator Training Effectiveness: A Meta-Analysis. Military Psychology, 4, 63-74.
http://dx.doi.org/10.1207/s15327876mp0402_1 [6] Salas, E., Rosen, M., Held, J. and Weissmuller, J. (2009) Performance Measurement in Simulation-Based Training: A Review and Best Practices. Simulation & Gaming, 40, 328-376.
http://dx.doi.org/10.1177/1046878108326734 [7] Dawley, L. and Dede, C. (2013) Situated Learning in Virtual Worlds and Immersive Simulations. In: Spector, J.M., Merrill, M.D., Elen, J. and Bishop, M.J., Eds., Handbook of Research on Educational Communications and Technology, New York, Springer, 723-734.
http://www.amazon.com/Handbook-Research-Educational-Communications-Technology/dp/1461431840 [8] Dutta, D. (1999) Simulation in Military Training: Recent Developments. Defense Science Journal, 49, 275-285.
http://dx.doi.org/10.14429/dsj.49.3840 [9] Stafford, R.J. and Thornhill, W.M. (2012) The Army Learning Model: Changing the Way Sustainers Train. Army Sustainment, 44, 28-31. [10] Linden Research, Inc. (2015) Second Life Official Site.
http://secondlife.com/ [11] Overte Foundation (2015) Main Page.
http://opensimulator.org/ [12] Mondesire, S.C., Stevens, J. and Maxwell, D.B. (In Press) Vertical Scalability Benchmarking in Three-Dimensional Virtual Worlds Simulation. Proceedings of the 2015 Summer Simulation Multi-Conference, Chicago, 26-29 July 2015. [13] Mondesire, S.C., Stevens, J. and Maxwell, D.B. (In Press) An Analysis of Increases Vertical Scaling in Three-Dimensional Virtual World Simulation. Proceedings of the 8th International Conference on Simulation Tools and Techniques, Athens, 24-26 August 2004. [14] Mondesire, S.C., Stevens, J. and Maxwell, D.B. (Submitted) Network Bandwidth’s Effect on Virtual World Simulator Performance Optimization. Proceedings of the 2015 Interservice/Industry Training, Simulation and Education Conference (I/ITSEC), Orlando, 30 November-4 December 2015. [15] Stevens, J., Mondesire, S.C., and Maxwell, D.B. (Submitted) Human Entities’ Effect on Server Performance in Distributed Virtual World Training. Proceedings of the 2015 Fall Simulation Interoperability Workshop, Orlando, 30 August-4 September 2015.