Dynamic Grid-Based Approach to Data Distribution Management |
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| Affiliation: | 1. Department of Materials Science and Engineering, Korea University, Seoul 136-713, Republic of Korea;2. R&D Center of Jahwa Electronics Co. Ltd., Cheongwon 363-922, Republic of Korea;3. Department of Advanced Materials Engineering, Sunmoon University, Asan 336-708, Republic of Korea;1. Faculty of Physics, Lomonosov Moscow State University, 119991 Moscow, Russia;2. Center for Functionalized Magnetic Materials (FunMagMa), Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia;3. Immanuel Kant Baltic Federal University, 236004 Kaliningrad, Russia;4. National University of Science and Technology MISiS, 119049 Moscow, Russia;5. Tver State University, 170100 Tver, Russia;1. School of Materials Science and Engineering, South China University of Technology, Guangzhou 510640, PR China;2. Guangdong Research Institute of Rare Metals, Guangzhou 510640, PR China;1. Institute of Solid State Physics, Russian Academy of Sciences, Chernogolovka, Russia;2. Karlsruher Institut für Technologie, Institut für Nanotechnologie, Eggenstein-Leopoldshafen, Germany;3. Laboratory of Hybrid Nanomaterials, National University of Science and Technology, MISIS, Moscow, Russia;4. Applied Physics II, University of the Basque Country UPV-EHU, Bilbao, Spain;1. Laboratory for Studies of Research and Technology Transfer, Institute for System Analysis and Computer Science (IASI-CNR), National Research Council of Italy, Via dei Taurini 19, 00185 Roma—Italy;2. Department of Engineering and Management—University of Rome “Tor Vergata” and Institute for System Analysis and Computer Science (IASI-CNR), Dip. di Ingegneria dell’Impresa, Via del Politecnico 1, 00133 Roma—Italy |
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| Abstract: | Data distribution management (DDM) is one of the services defined by the DoD High Level Architecture and is necessary to provide efficient, scalable mechanisms for distributing state updates and interaction information in large scale distributed simulations. In this paper, we focus on data distribution management mechanisms (also known as filtering) used for real time training simulations. We propose a new method of DDM, which we refer to as the dynamic grid-based approach. Our scheme is based on a combination of a fixed grid-based method, known for its scalability, and a region-based strategy, which provides greater accuracy than the fixed grid-based method. We describe our DDM algorithm, its implementation, and report on the performance results that we have obtained using the RTI-Kit framework. Our results clearly indicate that our scheme is scalable and that it reduces the message overhead by 40%, and the number of multicast groups used by 98% when compared to the fixed grid-based allocation scheme using 10 nodes, 1000 objects, and 20,000 grid cells. |
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