a relational database and key-value store combined mechanism for massive heterogeneous sensor data management

ISCAS OpenIR

	a relational database and key-value store combined mechanism for massive heterogeneous sensor data management
	Ding Zhiming; Yang Qi; Guo Limin
	2012
会议名称	1st International Conference on Sensor Networks, SENSORNETS 2012
会议录名称	SENSORNETS 2012 - Proceedings of the 1st International Conference on Sensor Networks
页码	151-154
会议日期	February 24, 2012 - February 26, 2012
会议地点	Rome, Italy
收录类别	EI
ISBN	9789898565013
部门归属	(1) Institute of Software Chinese Academy of Sciences South Fourth Str. 4 Zhongguancun Beijing 100190 China; (2) National Center ITS Engineering and Technology Xitucheng Road 8 Beijing 100088 China
摘要	Massive sensor data management is an important issue in large-scale sensor based systems such as the Internet/web of Things. However, existing relational database and cloud data management techniques are inadequate in handling large-scale sensor sampling data. On the one hand, relational databases can not efficiently process frequent data updates caused by sensor samplings. On the other hand, current cloud data management mechanisms are largely key-value stores so that they can not support complicated spatialtemporal computation involved in sensor data query. To solve the above problems, we propose a Relational Data-Base and Key-Value store combined Cloud Data management ("RDB-KV CloudDB") framework, in this paper. The experimental results show that the RDB-KV CloudDB can provide satisfactory query processing and sensor data updating performances in large scale sensor-based systems.; Massive sensor data management is an important issue in large-scale sensor based systems such as the Internet/web of Things. However, existing relational database and cloud data management techniques are inadequate in handling large-scale sensor sampling data. On the one hand, relational databases can not efficiently process frequent data updates caused by sensor samplings. On the other hand, current cloud data management mechanisms are largely key-value stores so that they can not support complicated spatialtemporal computation involved in sensor data query. To solve the above problems, we propose a Relational Data-Base and Key-Value store combined Cloud Data management ("RDB-KV CloudDB") framework, in this paper. The experimental results show that the RDB-KV CloudDB can provide satisfactory query processing and sensor data updating performances in large scale sensor-based systems.
关键词	Data Processing Database Systems Sensor Networks
主办者	Inst. Syst. Technol. Inf., Control Commun. (INSTICC)
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15691
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Ding Zhiming,Yang Qi,Guo Limin. a relational database and key-value store combined mechanism for massive heterogeneous sensor data management[C],2012:151-154.