基于服务力向量的发布/订阅自动发现算法  

Publish/Subscribe Automatic Discovery Algorithm Based on Service Ability Vector

作　　者：翟海波[1] 庄毅[1] 霍瑛[1] 

机构地区：[1]南京航空航天大学计算机科学与技术学院,南京210016

出　　处：《计算机工程》2014年第9期51-54,65,共5页Computer Engineering

基　　金：航空科学基金资助项目(2010ZC13012);江苏省普通高校研究生科研创新计划基金资助项目(CXZZ13_0171)

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。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.

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 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]