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Title:
seaclouddm: a database cluster framework for managing and querying massive heterogeneous sensor sampling data
Author: Ding Zhiming ; Xu Jiajie ; Yang Qi
Source: Journal of Supercomputing
Issued Date: 2012
Pages: 40933
Indexed Type: ei
Department: (1) Institute of Software, Chinese Academy of Sciences, South-Fourth-Street 4, Zhong-Guan-Cun, Beijing, 100190, China; (2) National Center of ITS Engineering and Technology, Xitucheng-Road. 8, Haidian District, Beijing, 100088, China
English Abstract: Recent advances in sensor networks and communication technologies have made the Internet of Things (IoT) a hot research issue. An IoT system can sample and manage the historical and present states of various kinds of physical and virtual objects such as vehicles, lakes, mountains, dams, city traffic conditions, atmosphere qualities, and so forth. It is well acknowledged that IoT will greatly change the way how people live and work. However, IoT also brings about great challenges to the data management community. For instance, the data to be managed in IoT are highly dynamic and heterogeneous. Meanwhile, since the sensor sampling data are managed in a centralized manner, the data size can be huge. Moreover, sensor data are intrinsically spatial-temporal data which may involve complicated spatial-temporal computations in query processing. To meet these challenges, we propose a novel Sea-Cloud-based Data Management (SeaCloudDM) mechanism in this paper. The experimental results show that the SeaCloudDM mechanism provides satisfactory performances in managing and querying massive sensor sampling data, and is thus a viable solution for IoT data management. © 2012 Springer Science+Business Media, LLC.
Language: 英语
WOS ID: WOS:000326805000009
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/14715
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Ding Zhiming,Xu Jiajie,Yang Qi. seaclouddm: a database cluster framework for managing and querying massive heterogeneous sensor sampling data[J]. Journal of Supercomputing,2012-01-01:40933.
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