摘要： 由于SDPBloom 自动发现算法无法预先在参与者发现阶段对端点QoS 策略的兼容性进行判断,使得各节点和网络中均出现大量QoS 不兼容的端点信息,从而消耗过多的内存和网络资源。为解决该问题,提出一种基于服务力向量(SAV)的发布/ 订阅自动发现算法,利用布隆过滤器向量和SAV 对端点主题名、主题类型以及QoS 策略进行匹配,以减少不必要信息的传输和存储。实验结果表明,与SDP_ADA 和SDPBloom 算法相比,该算法具有更低的网络负载和内存消耗。
关键词:
服务力向量,
发布/ 订阅,
数据分发服务,
自动发现算法,
布隆过滤器,
服务质量
Abstract: The SDPBloom automatic discovery algorithm can not judge Quality of Service (QoS) compatibility of
endpoints in the participants discovery phase in advance,and it makes probably a large number of QoS incompatible endpoints information on the each node and the network,which consumes too much memory and network resources. To solve this problem,this paper proposes an automatic discovery algorithm based on Service Ability Vector(SAV),which can judge whether the topic name and type of endpoints are matched and QoS compatibility by the Bloom Filter Vector (BFV) and SAV to reduce unnecessary information transmission and storage. Experimental results show that the algorithm has lower memory resource and network transmission consumption than SDP_ADA algorithm and SDPBloom algorithm.
Key words:
Service Ability Vector(SAV),
publish / subscribe,
Data Distribution Service(DDS),
automatic discovery
algorithm,
Bloom filter,
Quality of Service(QoS)
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