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A Proactive Service Model Facilitating Stream Data Fusion and Correlation

Yanbo Han, Chen Liu, Shen Su, Meiling Zhu, Zhongmei Zhang, Shouli Zhang

Source Title: International Journal of Web Services Research (IJWSR)14(3)

ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781522511137|DOI: 10.4018/IJWSR.2017070101

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MLA

Han, Yanbo, et al. "A Proactive Service Model Facilitating Stream Data Fusion and Correlation." IJWSR vol.14, no.3 2017: pp.1-16. http://doi.org/10.4018/IJWSR.2017070101

APA

Han, Y., Liu, C., Su, S., Zhu, M., Zhang, Z., & Zhang, S. (2017). A Proactive Service Model Facilitating Stream Data Fusion and Correlation. International Journal of Web Services Research (IJWSR), 14(3), 1-16. http://doi.org/10.4018/IJWSR.2017070101

Chicago

Han, Yanbo, et al. "A Proactive Service Model Facilitating Stream Data Fusion and Correlation," International Journal of Web Services Research (IJWSR) 14, no.3: 1-16. http://doi.org/10.4018/IJWSR.2017070101

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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.

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A Proactive Service Model Facilitating Stream Data Fusion and Correlation

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