Submission Deadline: 10 December 2017
IEEE Access invites manuscript submissions in the area of Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things.
With growing attention from both academia and industry, industrial internet of things (IIoT), comprised of a multitude of connected devices, is supposed to monitor, collect, exchange, analyze, and further instantly act on information to intelligently change the industrial device’s behavior or the industrial environment (e.g., autonomous reaction to unexpected changes in production by effectively detecting failures and triggering maintenance processes). In consideration of this goal, the convergence of sensor networks, cloud computing, and big data in IIoT is recently identified as an essential component. Specifically, sensor networks are deployed to capture various data in IIoT. Meanwhile, cloud computing platforms are developed to store and process data powerfully in IIoT. Moreover, big data analytics tools are utilized to glean valuable findings from the massive data in IIoT.
However, to integrate sensor networks, cloud computing, and big data in IIoT in a robust way, there are a lot of tough issues to be solved with respect to various aspects (e.g., framework, power efficiency, security, quality of service, etc.). Therefore, this Special Section in IEEE Access aims to solicit original technical papers with novel contributions on the convergence of sensor networks, cloud computing, and big data in IIoT. Review or survey type articles will also be considered. Submissions should focus on the convergence (i.e., the contemporaneous utilization of at least two of the three technologies – sensor networks, cloud computing, and big data in IIoT). Submissions that work on the experimental implementation of the convergence of sensor networks, cloud computing, and big data in IIoT are especially welcome.
Topics of interest include, but are not limited to:
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Associate Editor: Lei Shu, Guangdong University of Petrochemical Technology, China
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IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland
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