ACM Transactions on Programming Languages and Systems (TOPLAS)
Design and implementation of HLA time management in the RTI version F.0
Proceedings of the 29th conference on Winter simulation
Creating computer simulation systems: an introduction to the high level architecture
Creating computer simulation systems: an introduction to the high level architecture
Network aware time management and event distribution
PADS '00 Proceedings of the fourteenth workshop on Parallel and distributed simulation
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Parallel and Distribution Simulation Systems
Parallel and Distribution Simulation Systems
Data consistency in a large-scale runtime infrastructure
WSC '05 Proceedings of the 37th conference on Winter simulation
Development of a runtime infrastructure for large-scale distributed simulations
Proceedings of the 38th conference on Winter simulation
Implementation of time management in a runtime infrastructure
Proceedings of the 38th conference on Winter simulation
HLA-Based Parallel Simulation: A Case Study
PADS '12 Proceedings of the 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation
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The HLA time management is an important factor that limits the scalability of distributed simulations. An efficient algorithm of Greatest Available Logical Time (GALT) is thus much critical for the time management in an RTI to support large-scale simulations. The concept of GALT in IEEE 1516 was also called Lower Bound Time Stamp (LBTS) in HLA 1.3. The computation of GALT in the HLA time management is different from that of LBTS in traditional Parallel Discrete Event Simulation (PDES). In this paper, an algorithm about GALT is presented and its correctness is proved. Its efficiency is also explained by applying it to RTI1.3-NG. In fact, the algorithm has been implemented in our RTI to support thousands of federates in our cluster systems. In addition, a real-world example is introduced to explain the correctness of the algorithm proving, and the reason of our RTI supporting large-scale simulations.