Data distribution management for high performance distributed simulation in resource-constraint environment

Data Distribution Management (DDM) is responsible in parallel and distribution simulation, especially in large-scale distributed modeling and simulation applications, for limiting and controlling the data exchanged and reducing the processing requirements of federates. In high-performance distributed simulation, system scalability can be seriously inhibited by limits on resources such communication bandwidth, memory, and CPU availability. In this paper, we present the design and implementation of a resource-efficient enhancement to the P-Pruning algorithm for data distribution management problem in High Level Architecture. We also present a performance evaluation study in a memory-constraint environment. The Memory-Constraint P-Pruning algorithm deploys I/O efficient data-structures for optimized memory access at run-time. The simulation results show that the Memory-Constraint P-Pruning DDM algorithm is faster than the P-Pruning algorithm and utilizes memory at run-time more efficiently. It is suitable for high performance distributed simulation applications as it improves the scalability of the P-Pruning algorithm by several order in terms of number of federates.