DocumentCode :
271160
Title :
Spatial big data and wireless networks: experiences, applications, and research challenges
Author :
Jardak, Christine ; Mähönen, Petri ; Riihijärvi, Janne
Author_Institution :
Siemens Corp., Germany
Volume :
28
Issue :
4
fYear :
2014
fDate :
July-August 2014
Firstpage :
26
Lastpage :
31
Abstract :
In this article we demonstrate that spatial big data can play a key role in many emerging wireless networking applications. We also argue that spatial and spatiotemporal problems have their own very distinct role in the big data context compared to the commonly considered relational problems. We describe three major application scenarios for spatial big data, each imposing specific design and research challenges. We then present our work on developing highly scalable parallel processing frameworks for spatial data in the Hadoop framework using the MapReduce computational model. Our results show that using Hadoop enables highly scalable implementations of algorithms for common spatial data processing problems. However, development of these implementations requires significant specialized knowledge, demonstrating the need for development of more user-friendly alternatives.
Keywords :
mobile computing; very large databases; visual databases; Hadoop framework; MapReduce computational model; parallel processing framework; spatial big data; spatial data processing problem; spatio-temporal problem; wireless networks; Big data; Information retrieval; Sensors; Spatial analysis; Spatial databases; Wireless networks; Wireless sensor networks;
fLanguage :
English
Journal_Title :
Network, IEEE
Publisher :
ieee
ISSN :
0890-8044
Type :
jour
DOI :
10.1109/MNET.2014.6863128
Filename :
6863128
Link To Document :
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