文章基本信息

标题：Research on the Intelligent Composition and Selection Method for Semantic Web of Things Services
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作者：Xinying Chen ; Guanyu Li ; Yueping Zhang 等
期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2020
卷号：47
期号：3
语种：English
出版社：IAENG - International Association of Engineers
摘要：In order to find an effective composition and selection algorithm for Semantic Web of Things services, concepts, “optimal semantic matching for service bipartite graph”, “parameter dependency degree” and “set of Qos highquality solutions” are defined firstly. In the meanwhile, relevant theorems are drawn out. Then combined with characteristics of the service composition and selection problem, considering influence factors: the local semantic matching between subservices, the global semantic matching between demands and services, the dependencies between input and output parameters, and the Qos quality model for composite services, a quality evaluation model Qos(CS) for composite services is proposed here. After that, a dynamic service composition and selection algorithm IC&S SW T S is designed based on the quality evaluation model and genetic algorithm. With consideration of above factors, the new algorithm effectively solves problems in existing algorithms and further improves precision. Finally, theoretical analysis and experimental results reveal the validity of the proposed algorithm. And the algorithm provides reasonable approximate optimal solutions at lower costs.
关键词：semantic web of things services;semantic matching;dynamic service composition;bipartite graph matching;genetic algorithm