An integrated framework for managing massive and heterogeneous sensor data using cloud computing

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外文摘要：Cloud computing can provide a powerful， scalable storage and the massive data processing infrastructure to perform both online and offline analysis and mining of the heterogeneous sensor data streams。 With the recent explosion of wireless sensor networks and their applicability in military and civilian applications， there is an emerging vision for integrating sensor networks into the cloud computing platform。 In contrast to traditional data objects， the sensor data objects have continuously changed， high-dimensional， spatiotemporal relation and heterogeneous attributes。 Therefore， the management and processing problem of the massive sensor data objects can be more complicated。 The paper formally presents an integrated framework for managing massive and heterogeneous sensor data with insights into the high-dimensional problem using the map-reduce platform of cloud computing。 The proposed framework incorporates key concepts such as parallel-processing， scalability and flexibility of resources， sensor data uncertainty and the dynamic deployment and management of applications。

外文关键词：

Cloud computingMapReduceMassive sensor data managementParallel processing

作者：

Xin Song、Cuirong Wang、Yanjun Chen

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作者单位：

Computing Center, Northeastern University at Qinhuangdao, China

会议名称：

International Conference on Mechatronic Sciences, Electric Engineering and Computer

会议地点：

Shenyang(CN)

会议母体文献：

Proceedings 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer

页码：

461-464

出版时间：

2013

DOI：

10.1109/MEC.2013.6885113