摘要
该文介绍了一种有效的数据分布管理方法———模糊分组方法.为了提高数据分组精度、数据包过滤率和有效数据包接收率,控制匹配次数,该方法在模糊关联空间法基础上增加了模糊一致关系权值分配机制和基于格子的预分组.通过在飞行仿真系统中使用并与传统方法比较,说明模糊分组方法不仅在不同规模仿真环境中能够保证稳定的数据包过滤率及较高的有效数据包接收率,而且可有效控制匹配次数.
An efficient DDM (Data Distribution Management) method——fuzzy grouping method is presented. In order to reduce the matching number and increase the data filtering rates, meanwhile to keep high and stable relevant data reception rates, this new method added two new techniques based on the fuzzy correlation space approach: fuzzy consistent relation based weight distribution and grid based preprocessing. Simulation results show that fuzzy grouping method not only keeps high and stable data filtering rates in different situation but also greatly reduces matching number compared with existing methods.
出处
《计算机学报》
EI
CSCD
北大核心
2005年第7期1104-1109,共6页
Chinese Journal of Computers
基金
浙江省自然科学基金(Y104199)资助.~~
关键词
分布式仿真
数据分布管理
分组
数据过滤
模糊
distributed simulation
data distribution management
grouping
data filtering
fuzzy
