Research on the intelligent composition and selection method for semantic web of things services

被引：0

作者：

Chen, Xinying ^{[1
]}

Li, Guanyu ^{[2
]}

Zhang, Yueping ^{[3
]}

Liu, Yuefan ^{[3
]}

Sun, Yunhao ^{[4
]}

机构：

[1] School of Software Technology, Dalian Jiao Tong University, Dalian, LiaoNing,116021, China

[2] Faculty of Information Science and Technology, Dalian Maritime University, China

[3] Dalian Jiao Tong University, China

[4] Dalian Maritime University, China

来源：

IAENG International Journal of Computer Science | 2020年 / 47卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Internet of things - Graph theory - Semantic Web - Web services - Parameter estimation - Quality of service - Pattern matching - Quality control;

D O I：

暂无

中图分类号：

学科分类号：

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 SWTS 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. © International Association of Engineers.

引用

页码：420 / 430