A Proactive Service Model Facilitating Stream Data Fusion and Correlation

Yanbo Han, Chen Liu, Shen Su, Meiling Zhu, Zhongmei Zhang and Shouli Zhang
Additional contact information
Yanbo Han: Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, North China University of Technology, Beijing, China & Cloud Computing Research Center, North China University of Technology, Beijing, China
Chen Liu: Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, North China University of Technology, Beijing, China & Cloud Computing Research Center, North China University of Technology, Beijing, China
Shen Su: Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, North China University of Technology, Beijing, China & Cloud Computing Research Center, North China University of Technology, Beijing, China
Meiling Zhu: Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, North China University of Technology, Beijing, China, Cloud Computing Research Center, North China University of Technology, Beijing, China & School of Computer Science and Technology, Tianjin University, Tianjin, China
Zhongmei Zhang: Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, North China University of Technology, Beijing, China, Cloud Computing Research Center, North China University of Technology, Beijing, China & School of Computer Science and Technology, Tianjin University, Tianjin, China
Shouli Zhang: Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, North China University of Technology, Beijing, China, Cloud Computing Research Center, North China University of Technology, Beijing, China & School of Computer Science and Technology, Tianjin University, Tianjin, China

International Journal of Web Services Research (IJWSR), 2017, vol. 14, issue 3, 1-16

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.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://services.igi-global.com/resolvedoi/resolve ... 018/IJWSR.2017070101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jwsr00:v:14:y:2017:i:3:p:1-16

Access Statistics for this article

International Journal of Web Services Research (IJWSR) is currently edited by Liang-Jie Zhang

More articles in International Journal of Web Services Research (IJWSR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().