Imprecise Computation As An Enabler For Complex And Time Critical Hla Simulation Networks

A trend over the past years is that simulation systems for training are being connected in simulation networks, allowing the interaction of teams spread in distributed sites. By combining interconnected simulation systems the simulation complexity increases and may affect time-critical simulation tasks in a negative way. As a consequence, the training simulation objectives may not be met. The same problem may occur when performing, for example, mission rehearsal on site, since available computation resources are usually very limited in this scenario, or for a joint fires scenario, where the large and complex functional chain (including intelligence, C2, forward observer, pilots, etc.) may overload existing resources. In this work, the technique of imprecise computation in real-time systems (ICRS) to preserve time-critical simulation tasks is presented. The ICRS technique allows time-critical tasks to produce quicker solutions for approximate results and saves computational resources. This paper discusses the main advantages of the ICRS technique by a review of the commonly used optimization concepts built upon imprecise computation field. The paper ends with presenting a work-in-progress: An architectural solution for aligning ICRS with the High Level Architecture (HLA), standardized as the IEEE 1516-series.171179Steed, A., Oliveira, M., (2009) Networked Graphics: Building Networked Games and Virtual Environments, , Morgan-KaufmanStahre, B., Raalte, S.V., Heldal, I., Sketching techniques in virtual reality: Evaluation of texturing styles in an urban planning model (2008) Proceedings of VSMM 2008, pp. 230-238. , CyprusSchricker, B.C., Van Der Lippe, S.R., Using the high level architecture to implement selective- fidelity (2004) Proceedings of the 37th Annual Simulation Symposium (ANSS'04), 8p. , USAGross, D.C., (1999) Report from the Fidelity Implementation Study Group, , SISO-REF-002-1999Liu, J.W.S., Lin, K.J., Shih, W.K., Yu, A.C., Algorithms for scheduling imprecise computations (1991) IEEE Computer, 24 (5), pp. 58-68Liu, J.W.S., Shih, W.K., Lin, K.J., Bettati, R., Chung, J.Y., Imprecise computations (1994) Proceedings of IEEE, 82 (1), pp. 83-94Gao, K., Zhang, Y., He, S., Gao, W., Imprecise scheduling on scalable media stream delivery (2003) Proceedings of ICICS-PCM, 3, pp. 1351-1355Breuer, M.A., Multi-media applications and imprecise computation (2005) Proceedings of the 8th Euromicro Conference on Digital System Design - DSD, pp. 2-7Millan-Lopez, V., Feng, W., Liu, J.W.S., Using the imprecise-computation technique for congestion control on a real-time traffic switching element (1994) International Conference on Parallel and Distributed Systems - ICPADS, pp. 202-208Chen, X., Cheng, A.M.K., An imprecise algorithm for real-time compressed image and video transmission (1997) Sixth International Conference on Computer Communications and Networks, pp. 390-397Tung, L.P., Chen, J.M., Hsu, W.F., Shih, W.K., An imprecise computation model in reducing power consumption of flash memory for portable devices (2004) Proceedings of the 28th Annual International Computer Software and Applications Conference - COMPSAC, pp. 62-63Nakanishi, F., Hiraike, S., Inoue, S., Kakuda, Y., Toda, K., A flexible scheduling for automobile control using imprecise computation and its fundamental evaluation (2000) Proc. 6th IEEE International Conference on Complex Computer System, pp. 210-217. , WashingtonMöller, B., Johansson, M., Hla evolved hands-on (2014) Pitch Technologies AB, 211pGustavsson, P.M., Björk Å., Brax, C., Planstedt, T., Towards service oriented simulations (2004) Falls Simulation Interoperability Workshop, 14p. , Orlando, Florida U.S.ASzwarcman, D., Feijó, B., Costa, M., Goal-oriented dead reckoning for autonomous characters (2001) Computers & Graphics, 25 (6), pp. 999-101