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A Proactive Service Model Facilitating Stream Data Fusion and Correlation

Authors :
Shouli Zhang
Yanbo Han
Zhongmei Zhang
Meiling Zhu
Chen Liu
Shen Su
Source :
International Journal of Web Services Research. 14:1-16
Publication Year :
2017
Publisher :
IGI Global, 2017.

Abstract

Stream data from devices and sensors is considered a typical kind of big data. Though being promising, they have a good prospect only when we can reasonably correlate and effectively use them. Herein, services come back to the spotlight. The paper reports some of the authors' efforts in promoting service-based fusion and correlation of such stream data in a real setting – monitoring and optimized coordination of individual devices in a power plant. This paper advocates a decentralized and service-based approach to dynamically correlating the sensor data and proactively generating higher-level events between sensors and applications. A novel service model for transforming and correlating massive stream data is proposed. This service model shows potential in realizing various middle-way programmable nodes to form larger-granularity and software-defined ‘sensors' in an IoT context.

Details

ISSN :
15465004 and 15457362
Volume :
14
Database :
OpenAIRE
Journal :
International Journal of Web Services Research
Accession number :
edsair.doi...........f8126473b8273226ffa788942ac8ef34