An Experimental Platform for Data Management in Distributed Simulation

In the High Level Architecture (HLA) paradigm, the Runtime Infrastructure (RTI) is similar to a distributed operating system for the simulation federates. The RTI provides a set of services, such as data distribution and management (DDM) among federates. Each federate may inform the RTI about its intention to publish some data, or it may subscribe to receive a subset of the published data. For example, in war gaming a tank may regularly publish its position and another object, e.g., an aircraft, may be interested to detect the position of the tank by subscribing to receive the position update data published by the tank. The goal of the DDM module in RTI is to make the data communication more efficient by sending the data only to those federates who need the data, as opposed to the broadcasting mechanism employed by Distributed Interactive Simulation (DIS). The approaches used by DDM are aimed at reducing the communication over the network, and the data set required to be processed by the receiving federates. Efficient data distribution is an important issue in large scale distributed simulations with several thousands of entities. The broadcasting mechanism employed in Distributed Interactive Simulation (DIS) standards generates unnecessary network traffic and is not suitable for large scale and dynamic simulations. An efficient data distribution mechanism should filter the data and forward only those data to federates who need the data. Several filtering mechanisms have appeared in the literature and some of them have been implemented in RTI. In this paper, we will briefly describe these mechanisms. We describe the design and implementation of a simulation platform used to investigate one of these mechanisms, the grid-based filtering mechanism, and report on the initial experimental results. We show that the size of the grid cells has a substantial impact on the performance of distributed simulations. This platform will serve as a tool for further experimentation on grid-based and other filtering mechanisms.