Abstract
The time management model for event processing in internet of things has a special and important requirement. Many events in real world applications are long-lasting events which have different time granularity with order or out-of-order. The temporal relationships among those events are often complex. An important issue of complex event processing is to extract patterns from event streams to support decision making in real-time. However, current time management model does not consider the unified solution about time granularity, time interval, time disorder, and the difference between workday calendar systems in different organizations. In this work, we analyze the preliminaries of temporal semantics of events. A tree-plan model of out-of-order durable events is proposed. A hybrid solution is correspondingly introduced. A case study is illustrated to explain the time constraints and the time optimization. Extensive experimental studies demonstrate the efficiency of our approach.
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Acknowledgement
This research was partially supported by the Project of Shandong Province Higher Educational Science and Technology Program (J12LN05); the National Natural Science Foundation of China (Grant Nos. 61202111, 61472141, 61273152, 61303017); the Project Development Plan of Science and Technology of Yantai City (2013ZH092); the Doctoral Foundation of Ludong University (LY2012023); the Natural Science Foundation of Shandong (ZR2016FM15).
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Chunjie Zhou received the PhD degree in computer science from Renmin University of China in 2011. She is currently a researcher and associate professor with the Department of Computer Science at Ludong University, China. She has published more than 30 academic papers in peer-reviewed international journals and conferences. Her research interests include big data, data mining, internet of things, and cloud computing.
Xiaoling Wang received the BS, MS, and PhD degrees from Southeast University, China in 1997, 2000, and 2003, respectively, all in computer science. She is currently a professor with East China Normal University, China. She has published more than 100 papers in peer-reviewed international journals and conferences, such as JWSR, JCST, SIGMOD, IJCAI, WWW, SIGIR, ICWS, DASFAA. Her current research interests include Web data management and data mining.
Zhiwang Zhang received the PhD degree in computer science from Chinese Academy of Sciences, China in 2009. He is currently a researcher and associate professor with the Department of Computer Science at Ludong University, China. He has published over 30 academic papers in various international journals and conferences. His research interests are in the areas of data mining and knowledge discovery, forecasting, machine learning, optimization, artificial intelligence and natural language processing.
Zhenxing Zhang received the BS degree in computer science from Shandong university of technology, China in 2005. He received his the MS degree and PhD degree from the IT collge, Gachon University of SouthKorea, in 2008 and 2012. He is currently an assistant professor in Ludong University. His research focuses on machine learning, biomedical prediction systems, multimedia content analysis and computational linguistics.
Haiping Qu received his PhD in Computer Science and Technology from the Institute of Computing Technology, Chinese Academy of Sciences (CAS), China in 2011. He is currently a lecturer in the School of Information and Electrical Engineering, Ludong University, China. His research interests include cloud computing and big data processing.
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Zhou, C., Wang, X., Zhang, Z. et al. The time model for event processing in internet of things. Front. Comput. Sci. 13, 471–488 (2019). https://doi.org/10.1007/s11704-018-7378-4
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DOI: https://doi.org/10.1007/s11704-018-7378-4