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A Proactive Service Model Facilitating Stream Data Fusion and Correlation

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  • 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)

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.

Suggested Citation

  • Yanbo Han & Chen Liu & Shen Su & Meiling Zhu & Zhongmei Zhang & Shouli Zhang, 2017. "A Proactive Service Model Facilitating Stream Data Fusion and Correlation," International Journal of Web Services Research (IJWSR), IGI Global, vol. 14(3), pages 1-16, July.
    • Handle: RePEc:igg:jwsr00:v:14:y:2017:i:3:p:1-16
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