DocumentCode
162491
Title
LSD2H: A Novel Storage Method of Linked Sensor Data Based on HBase
Author
Hongbin Gao ; Dongfeng Wang
Author_Institution
Sch. of Inf. Sci. & Eng., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
fYear
2014
fDate
27-29 Aug. 2014
Firstpage
116
Lastpage
119
Abstract
With the development of sensor network, the number of sensors are increasing now. In order to manage sensor data, W3C has proposed semantic sensor web which unifies sensor network data and produces massive RDF dataset. Linked Sensor Data is a normal dataset of semantic sensor web and links into Linked Open Data based on SSN ontology. HBase is a kind of distributed database and suits for the management of Linked Sensor Data applicably. So we propose LSD2H which is a storage method of Linked Sensor Data by use of HBase. LSD2H architecture consists of SDS, ODS, SD2H, OD2H and SCQuery. SDS is a table in HBase for storing sensor data. ODS is a table in HBase for storing observation data. SD2H maps Linked Sensor Data to SDS, while OD2H maps Linked Sensor Data to ODS by MapReduce. SCQuery based on tree pattern and recursion algorithm is a query method about SDS and ODS. In order to deduce storage space and improve query performance, we analyze the compression algorithms of LZO, GZIP, Snappy and no compression, which has proved that LZO selected by using storage of data is benefit for LSD2H in final.
Keywords
data handling; query processing; semantic Web; GZIP; HBase; LSD2H; LZO; MapReduce; OD2H; ODS; SCQuery; SDS; SSN ontology; Snappy; W3C; compression algorithms; distributed database; linked open data; linked sensor data; massive RDF dataset; query method; query performance; recursion algorithm; semantic sensor Web; sensor data management; sensor network data; storage method; storage space deduction; tree pattern; Algorithm design and analysis; Distributed databases; Educational institutions; Google; Indexes; Resource description framework; Semantics; HBase; Hadoop; Linked Sensor Data; MapReduce; Semantic Sensor Web;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantics, Knowledge and Grids (SKG), 2014 10th International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/SKG.2014.31
Filename
6964674
Link To Document