Abstract
We are living in a sensor-rich world. However, managing, accessing and analyzing the collective worldwide sensors’ spatio-temporal observations in a coherent manner is very challenging. That is because the large number of sensors are distributed all over the world and each sensor provides large volume of continuous observations over the time. Our objective in this paper is to construct a scalable data service for gathering and accessing the worldwide sensors’ collective observations. Our proposed solution has a hybrid architecture consisting of local services and a Cloud storage. In our solution, we combine a cloud-based scale out geospatial data stream architecture with the LOST-tree indexing structure. Our initial experiment shows that such hybrid structure is scalable and efficient for sensor data write, local search and global historical search.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Huang, C.-Y., Liang, S.H.L.: Lost-tree: a spatio-temporal structure for efficient sensor data loading in a sensor web browser. Int. J. Geogr. Inf. Sci. 27(6), 1190–1209 (2013)
Lee, D.W., Liang, S.H.L.: Geopot: a cloud-based geolocation data service for mobile applications. Int. J. Geogr. Inf. Sci. 25(8), 1283–1301 (2011)
Li, Q., Zhang, T., Yu, Y.: Using cloud computing to process intensive floating car data for urban traffic surveillance. Int. J. Geogr. Inf. Sci. 25(8), 1303–1322 (2011)
Wang, Y., Wang, S., Zhou, D.: Retrieving and indexing spatial data in the cloud computing environment. In: Jaatun, M.G., Zhao, G., Rong, C. (eds.) Cloud Computing. LNCS, vol. 5931, pp. 322–331. Springer, Heidelberg (2009)
Liang, S.H.L., Huang, C.Y.: Geospatial Cyberinfrastructure for Addressing the Big Data Challenges on the Worldwide Sensor Web. Big Data: Techniques and Technologies in Geoinformatics. CRC Press, Boca Raton (2014)
Evans, D.: The internet of things: How the next evolution of the internet is changing everything. CISCO white paper (2011)
Zheng, Y.: Tutorial on location-based social networks. In: WWW 2012, (2012)
Rigaux, P., Scholl, M., Voisard, A.: Spatial Databases: with Application to GIS. Morgan Kaufmann, Burlington (2001)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Khalafbeigi, T., Huang, CY., Liang, S., Wang, M. (2014). A Hybrid Scale-Out Cloud-Based Data Service for Worldwide Sensors. In: Han, WS., Lee, M., Muliantara, A., Sanjaya, N., Thalheim, B., Zhou, S. (eds) Database Systems for Advanced Applications. DASFAA 2014. Lecture Notes in Computer Science(), vol 8505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43984-5_26
Download citation
DOI: https://doi.org/10.1007/978-3-662-43984-5_26
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-43983-8
Online ISBN: 978-3-662-43984-5
eBook Packages: Computer ScienceComputer Science (R0)