Journal of System Simulation
Abstract
Abstract: The simulation test and evaluation of intelligent system of systems, systems and single equipment is a complex system engineering, which requires effective management of multi-source, heterogeneous and distributed massive simulation resources scattered in cloud test centers and test sites of various units; and good control of dynamically generated tasks, assumptions, configurations, results, evaluations and other data and files. The traditional way of managing and querying simulation resources by category is inefficient and difficult to meet the requirements of large-scale intelligent simulation test and evaluation activities. An overall framework for simulation resource management based on graph association organization, defines a simulation resource association organization metamodel for graph association organization, and proposes key algorithms and methods for dynamically extracting simulation resource information managed in different tools/systems, constructs a simulation resource graph structure based on association organization, and provides on-demand access to simulation resources. Verified by application examples, this method can accurately mark the state changes of simulation resource sets that can affect the simulation operation results during the intelligent evolution process, and effectively improve the efficiency of simulation resource management and retrieval.
Recommended Citation
Liu, Zewei; Ding, Yishan; Lin, Tingyu; Ke, Mingxing; Guo, Liqing; Xiao, Yingying; Zhao, Zhilong; Li, Yan; and Lü, xuan
(2024)
"Research on Simulation Resource Management Based on Graph Association Organization,"
Journal of System Simulation: Vol. 36:
Iss.
9, Article 1.
DOI: 10.16182/j.issn1004731x.joss.24-0455
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol36/iss9/1
First Page
1984
Last Page
1994
CLC
TP311.52
Recommended Citation
Liu Zewei, Ding Yishan, Lin Tingyu, et al. Research on Simulation Resource Management Based on Graph Association Organization[J]. Journal of System Simulation, 2024, 36(9): 1983-1994.
DOI
10.16182/j.issn1004731x.joss.24-0455
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons