DocumentCode
3020137
Title
An integrated framework for managing massive and heterogeneous sensor data using cloud computing
Author
Xin Song ; Cuirong Wang ; Yanjun Chen
Author_Institution
Comput. Center, Northeastern Univ. at Qinhuangdao, Qinhuangdao, China
fYear
2013
fDate
20-22 Dec. 2013
Firstpage
461
Lastpage
464
Abstract
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.
Keywords
cloud computing; data handling; parallel processing; MapReduce platform; cloud computing; dynamic deployment; heterogeneous sensor data management; high-dimensional data problem; massive data processing infrastructure; parallel processing; sensor data uncertainty; Cloud computing; Data mining; Data processing; Distributed databases; Dynamic scheduling; Parallel processing; Wireless sensor networks; Cloud computing; MapReduce; Massive sensor data management; Parallel processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on
Conference_Location
Shengyang
Print_ISBN
978-1-4799-2564-3
Type
conf
DOI
10.1109/MEC.2013.6885113
Filename
6885113
Link To Document