摘要
在分布式仿真系统中 ,网上流动的大量冗余数据严重影响了系统的可伸缩性。基于均匀网格的相关过滤法减少了冗余数据 ,但具有匹配不精确 ,格子尺寸单一 ,难以适应所有实体的缺点。提出了一种基于多层次网格的相关过滤方法 ,克服了均匀网格法的上述缺点 ,并继承了均匀网格法处理速度快的特点 。
In the distributed simulation system, lots of redundant data flowing on the net seriously restricts the system scalability. The relevance filtering base on even-grid reduces the redundant data while it is inaccurate in region matching. Because the sizes of all cells in even-grid are identical, it is difficult to fit all entities in the simulation. A relevance filtering method based on a multi-level grid is put forward which overcomes the above shortcomings and is characterized by agility and speediness.
出处
《国防科技大学学报》
EI
CAS
CSCD
北大核心
2002年第4期48-52,共5页
Journal of National University of Defense Technology
基金
国家 8 6 3高技术资助项目 ( 2 0 0 1AA115132 )