After Action Review System development trends
WSC '95 Proceedings of the 27th conference on Winter simulation
Transparent incremental state saving in time warp parallel discrete event simulation
PADS '96 Proceedings of the tenth workshop on Parallel and distributed simulation
Automatic incremental state saving
PADS '96 Proceedings of the tenth workshop on Parallel and distributed simulation
Issues in the Design of a Reflective Library for Checkpointing C++ Objects
SRDS '99 Proceedings of the 18th IEEE Symposium on Reliable Distributed Systems
Incremental checkpointing with application to distributed discrete event simulation
Proceedings of the 38th conference on Winter simulation
The Multi-Agent Data Collection in HLA-Based Simulation System
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
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The data collection in simulations is important especially for the use in After Action Review (AAR). In distributed simulations there is still not a standardized solution for data collection. The main reason is the diversity of the simulations and the new developments in this area. It was less complicated to collect simulation data with DIS standard; but the relatively new standard, HLA, not only has come with the optimizations, reusability and more interoperability but also with the complication and overhead of data collection. With the use of HLA, the simulation's state data has got along together more in simulators/federates own domain rather than being emitted to the simulation network. So, a solution for collecting this important private data should also be introduced. We first examine the need of data collection, especially in AAR; then overview the possible solutions, with their pros and cons and argue how a robust data collection can be achieved. After that, the proposed and implemented architecture is described. The paper ends with the benchmarking results.