面向大规模空间Agent建模的分布式地理模拟框架

A Distributed Geospatial Simulation Framework for Massive Spatial Agent-Based Modeling

基于Agent建模的地理模拟是认识和理解动态地理现象的有效方法,但随着地理模拟的规模和复杂性不断增加,模型的计算问题开始凸显。分布式并行仿真是解决大规模Agent复杂模拟计算的途径,然而已有研究基于Agent建模/仿真软件构建并行仿真系统的方式并不适用于具有高移动与行为交互的空间Agent建模及其模拟过程的实时可视化。为解决这个问题,本文提出了一个分布式地理模拟框架DGSimF,用于大规模动态空间Agent模拟,支持模拟过程的实时表示与分析。设计了一个简单但高效的时空数据模型建模空间Agent,支持直接基于Agent行为建模集成地学模型,采用了时间微分方法协同各计算节点行为的执行,实现以“任务并行”的方式进行分布式计算以提高仿真性能,构建了基于三维地球渲染引擎的虚拟地理环境,提供模拟过程的实时可视化。最后,以“红蓝对抗”案例进行了实验验证,对不同模拟计算量和不同客户端数量下的仿真性能进行了分析,结果表明DGSimF可以为具有时空特征变化与行为交互的大规模空间Agent模拟提供一个有效的平台。通过扩展计算节点,DGSimF可以有效地缓解复杂模拟计算的压力问题,并且仿真性能较高,在实验中并行效率保持在0.7以上。

Geospatial simulation based on agent-based modeling is an effective method to recognize and understand dynamic geographic phenomena.As the scale and complexity of geospatial simulation continues to increase,the challenges in model computation increase.Distributed parallel simulation could be used to solve the complex simulation issue of large-scale agents.However,the existing research on building parallel simulation system based on agent modeling/simulation software is not suitable for modeling of spatial agent with highmobility and behavioral interaction with others,and real-time visualization of simulation process.To solve this problem,this paper proposes a distributed geospatial simulation framework,namely DGSimF,for massive dynamic spatial agent modeling,which supports real-time representation and analysis of the simulation process.A simple but efficient spatial modeling agent for spatial-temporal data is designed,which supports the modeling of integrated geoscience models directly based on agent behavior,adopts the time differentiation method to coordinate the execution of the behavior of each computing node,supports distributed computation in the way of"task parallel"to improve the simulation performance,and constructs a Virtual Geographic Environment(VGE)based on three-dimensional earth rendering engine to support real-time visualization of intermediate simulation results.Finally,the experiments based on the"Red vs.Blue"case are carried out,and the simulation performance with different computation cost and different number of clients is analyzed.The results show that DGSimF can provide an effective platform for massive spatial agent simulation of spatio-temporal feature change and behavior interaction.By expanding the computing nodes,the pressure of complex simulation calculation can be effectively alleviated.Meanwhile,the simulation performance of the proposed framework is high,and the parallel efficiency remains above 0.7 in these experiments.