DocumentCode :
653211
Title :
IOT-StatisticDB: A General Statistical Database Cluster Mechanism for Big Data Analysis in the Internet of Things
Author :
Zhiming Ding ; Xu Gao ; Jiajie Xu ; Hong Wu
Author_Institution :
Inst. of Software, Beijing, China
fYear :
2013
fDate :
20-23 Aug. 2013
Firstpage :
535
Lastpage :
543
Abstract :
In large scale Internet of Things (IoT) systems, statistical analysis is a crucial technique for transforming data into knowledge and for obtaining overall information about the physical world. However, most existing statistical analysis methods for sensor sampling data are implemented outside the database kernel and focus on specialized analytics, making them unsuited for the IoT environment where both the data types and the statistical queries are diverse. To solve this problem, we propose a General Statistical Database Cluster Mechanism for Big Data Analysis in the Internet of Things (IOT-StatisticDB) in this paper. In IOT-StatisticDB, statistical functions are performed through statistical operators inside the DBMS kernel, so that complicated statistical queries can be expressed in the standard SQL format. Besides, statistical analysis is executed in a distributed and parallel manner over multiple servers so that the performance can be greatly improved, which is confirmed by the experiments.
Keywords :
Big Data; Internet of Things; SQL; data analysis; sampling methods; IOT-StatisticDB; Internet of Things; IoT systems; SQL format; Structured Query Languages; big data analysis; general statistical database cluster mechanism; sensor sampling data; statistical analysis methods; statistical queries; Databases; Global Positioning System; Internet; Memory; Monitoring; Servers; Statistical analysis; Big Data; Internet of Things; Sensor Sampling Data; Spatial-Temporal Data; Statistical Database;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/GreenCom-iThings-CPSCom.2013.104
Filename :
6682118
Link To Document :
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