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A Scalable Data Distribution Management Approach

机译:可扩展的数据分发管理方法

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摘要

Using Data Distribution Management (DDM), federates can send/receive interest data properly instead of broadcasting data over entire network. For large-scale HLA simulations with many simulation entities or federates, the use of DDM is essential to support such simulations. However, the scalability issue of DDM is rarely raised in the literature. Thus we present a scalable DDM approach, DHT-DDM, using Content-Addressable Networks (CANs) [1] based on Distributed Hash Table (DHT). Region declaration, region matching, and network connection mechanisms for DDM are designed considering scalability. The declaration of regions is done deterministically without depending on global information, the load of region matching is distributed and shared among federates, and the connections of federates is built upon application-level multicast.
机译:使用数据分发管理(DDM),联盟可以正确发送/接收兴趣数据,而不用在整个网络上广播数据。对于具有许多仿真实体或联盟的大规模HLA仿真,使用DDM对支持此类仿真至关重要。但是,文献中很少提出DDM的可伸缩性问题。因此,我们使用基于分布式哈希表(DHT)的内容可寻址网络(CAN)[1],提出了一种可扩展的DDM方法DHT-DDM。设计DDM的区域声明,区域匹配和网络连接机制时要考虑可伸缩性。区域声明是确定性地完成,而不依赖于全局信息,区域匹配的负载在联盟之间分配和共享,并且联盟的连接建立在应用程序级多播之上。

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