An approach to discovering event correlations among edge sensor services

被引:0
|
作者
Liu C. [1 ,2 ]
Cao Y. [1 ,2 ]
Han Y. [1 ,2 ]
机构
[1] Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, North China University of Technology, Beijing
[2] Institute of Data Engineering, School of Computer Science and Technology, North China University of Technology, No. 5 Jinyuanzhuang Road, Beijing
来源
Liu, Chen (liuchen@ncut.edu.cn) | 1600年 / Inderscience Publishers卷 / 07期
基金
中国国家自然科学基金;
关键词
Event correlation; Fog computing; Proactive data service; Sensor data; Service hyperlinks;
D O I
10.1504/IJIMS.2020.110229
中图分类号
学科分类号
摘要
In an IoT environment, a surge in sensor data volume has exposed the shortcomings of cloud computing, particularly the limitation of network transmission capability and centralised computing resources. To handle these issues, this paper proposes a service-oriented framework, called as INFOG, to support the dynamic cooperation among sensors with the fog computing paradigm. Proactive data services and service hyperlinks, which are our previous work, are two key abstractions for the INFOG framework. The services are software-defined abstraction of physical sensors. They are deployed in edge nodes in INFOG. And service hyperlinks, encapsulation of service correlations, enable the cooperation of sensors at the software layer. We also propose a frequent sequential pattern-based approach to effectively discover service hyperlinks. Based on the dataset from a real power plant as well as several synthetic datasets, we do lots of experiments to verify the effectiveness and efficiency of our algorithm. © 2020 Inderscience Enterprises Ltd.
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页码:358 / 374
页数:16
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