基于权重函数的混合DDM算法

高层体系结构已成为分布式仿真通用技术框架的核心,其中数据分发管理服务则为其提供了有效的数据过滤机制.目前常用的几种DDM算法,如基于区域的算法、基于网格的算法和简单混合的算法(基于网格的DDM和基于区域的DDM混合使用)等都存在着一些不足.基于权重函数的混合DDM算法是在简单混合的DDM算法基础上加入了对路经空间中所划分网格的权重函数设立机制和对冗余信息、虚假信息的控制机制.实验结果表明,该算法在减少算法执行时间,尤其是降低网络中的数据传输量和减少组播地址消耗方面,体现出良好的性能,进一步满足了系统的可扩缩性要求.

Hybrid DDM algorithm based on weight function

HLA has become the focus of distributed interactive simulation's general technology frame.Data distribution management, one of the six services,provides data filtering mechanism to meet the requirements of system sealability.Currently,there are several main DDM filtering algorithms.Since each approach still has some shortcomings,a hybrid DDM method is introduced based on weight function by which the redundant and false information is reduced greatly.Simulation experiments show that usually the weight function- based hybrid algorithm has the best performance among all approaches,especially on reducing the amount of data transformation and multicast address.It has achieved the goal of improving DDM.