Abstract
The rapid development of IoT has brought life around us with tremendous impact. Especially, industrial IoT as a new research hotspot, has been attracting extensive concern from industry and academia, facilitating many technologies and application in industrial IoT. However, taking full advantage of a large number of resources in industrial IoT is a challenging task. In this article, we present an efficient mobile social cluster algorithm (OMSC) to detect the potential social relationships among mobile devices in industrial IoT. It can discover the overlapping cluster and hierarchical structure in near-line time. We implement this algorithm in the Java Platform and validate the OMSC in synthetic networks and real-world network datasets. The experimental results demonstrate that the presented OMSC algorithm has high performance.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China under Grant No. 61103234 and No. 61272417, the China Scholarship Council and the Fundamental Research Funds for the Central Universities under Grant No. DUT16QY18.
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Luo, J., Lin, K., Wang, W. (2016). A Novel Algorithm for Detecting Social Clusters and Hierarchical Structure in Industrial IoT. In: Wan, J., Humar, I., Zhang, D. (eds) Industrial IoT Technologies and Applications. Industrial IoT 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 173. Springer, Cham. https://doi.org/10.1007/978-3-319-44350-8_17
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DOI: https://doi.org/10.1007/978-3-319-44350-8_17
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