基于单哈希计数布隆的DDS自动发现算法

DDS automatic discovery algorithm based on single hash count Bloom

针对DDS简单自动发现算法中网络传输量大、内存消耗高以及端点匹配时间长的问题,提出一种基于单哈希计数布隆过滤器的DDS自动发现算法——SDP_OHCBF。通过将标准布隆过滤器升级为计数布隆过滤器以支持元素删除操作,使用单个哈希函数和取模运算代替标准布隆过滤器中的多个哈希运算,加快布隆过滤器的元素查询过程。仿真验证结果表明,该算法降低了DDS自动发现过程的网络传输量与内存消耗,支持元素删除操作,提高了数据发布/订阅的实时性。

Aiming at the problems of large amount of network transmission data,high memory consumption and long endpoint matching time in the DDS simple automatic discovery algorithm,a DDS automatic discovery algorithm based on a single hash counting Bloom filter(SDP_OHCBF)was proposed.The standard Bloom filter was upgraded to a counting Bloom filter to support element deletion operations.To speed up the element query process of the Bloom filter,the single hash function and the modulo operation were used to replace multiple hash operations in the standard Bloom filter.The simulation verification results show that the proposed algorithm can reduce the network transmission volume and memory consumption of the DDS automatic discovery process.The proposed algorithm can support element deletion operations and improve the real-time performance of data publishing/subscription.