哈尔滨工业大学计算机科学与技术学院,黑龙江,哈尔滨,150001
纸质出版:2014
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周文平, 唐好选, 季振洲. 一种环境理解的分布式群体仿真任务划分方法[J]. 电子学报, 2014,42(12):2448-2456.
ZHOU Wen-ping, TANG Hao-xuan, JI Zhen-zhou. An Environment Structure Understanding Task Partition Method for Distributed Crowd Simulation[J]. Acta Electronica Sinica, 2014, 42(12): 2448-2456.
周文平, 唐好选, 季振洲. 一种环境理解的分布式群体仿真任务划分方法[J]. 电子学报, 2014,42(12):2448-2456. DOI: 10.3969/j.issn.0372-2112.2014.12.017.
ZHOU Wen-ping, TANG Hao-xuan, JI Zhen-zhou. An Environment Structure Understanding Task Partition Method for Distributed Crowd Simulation[J]. Acta Electronica Sinica, 2014, 42(12): 2448-2456. DOI: 10.3969/j.issn.0372-2112.2014.12.017.
本文通过引入环境结构因素
提出了一种适用于多层次复杂环境的自适应任务划分算法.自动读取场景模型并通过理解转换为连通邻接区域集
然后对区域进行快速粗粒度划分
有效提高划分性能;自然消除了被障碍隔离的相邻区域个体间的感知计算
大大减少了节点间通信量
使之更适合于大规模群体仿真应用.实验结果表明该算法的划分代价和执行性能均较优.文中设计了一种适合该划分算法的分布式仿真模型
基于该模型的分布式系统对室内多层楼宇或室外场景大规模群体仿真均具有较高仿真性能
相同规模群体的仿真性能与仿真节点数成线性关系表明系统具有良好的可扩展性.
The paper proposed an adaptive partition method considering environmental structural factors
which is applicable for multilayered complex environment.Simulation scene is automatically extracted to walkable adjacent areas
and a coarse granularity partition based on regions is applied to get shorter execution time.The inter-individual perceptual computing of any two individuals separated by obstacle between two adjacent regions is negligible
so it efficiently reduces the inter-node communication cost and makes the algorithm more suitable for large scale crowd simulation.The results show the proposed algorithm gets lower cost and higher performance.An efficient distributed simulation model is designed for the partition method
and a distributed system based on the model gets higher simulation performance on both inner door and out door scene.The performance of system with the same crowd size linearly increases with the increase of compute nodes
which proves high scalability of the system.
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