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2019 | OriginalPaper | Chapter

Runtime Service Composition Modification Supporting Situational Sensor Data Correlation

Authors : Chen Liu, Zhongmei Zhang, Shouli Zhang, Yanbo Han

Published in: Service-Oriented Computing – ICSOC 2018 Workshops

Publisher: Springer International Publishing

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Abstract

Although IoT service and service composition provide effective means to develop IoT applications, the dynamic and time-varying correlation among massive sensors rises up new challenges to the traditional model-based approaches, and the extra uncertainty and complexity of service composition become apparent. This paper proposes a data-driven service composition method based on our previous proactive data service model. We utilize real-time correlation analysis of sensor data to refine model-based service composition at runtime. The correlation among sensor data is usually asynchronous. In this paper, we adopt and improve a Dynamic Time Warping (DTW) algorithm to obtain one-way lag-correlation, and realize dynamic sensor data correlation through refining existing service composition. Based on the real sensor data set in a coal-fired power plant, a series of experiments demonstrate the effectiveness of our service composition method.

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Title: Runtime Service Composition Modification Supporting Situational Sensor Data Correlation
Authors: Chen Liu
Zhongmei Zhang
Shouli Zhang
Yanbo Han
Publisher: Springer International Publishing
Book: Service-Oriented Computing – ICSOC 2018 Workshops
Print ISBN: 978-3-030-17641-9

Electronic ISBN: 978-3-030-17642-6

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-17642-6_15

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