DocumentCode
3534755
Title
Radar networking in Collaborative Adaptive Sensing of Atmosphere: State of the art and research challenges
Author
Dilum Bandara, H.M.N. ; Jayasuman, A.P. ; Zink, M.
Author_Institution
Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO, USA
fYear
2012
fDate
3-7 Dec. 2012
Firstpage
1378
Lastpage
1383
Abstract
Collaborative Adaptive Sensing of the Atmosphere (CASA), in which a network of small weather radars collaborates in real time, has emerged as the preferred alternative for accurately detecting and tracking hazardous weather phenomena such as tornados. We address data transport and multi-sensor data fusion solutions proposed in context of CASA, focusing on their ability to support streaming and data pull modes of radar data access. How CASA can leverage emerging technologies, such as Named Data Networking (NDN), virtualization, and cloud computing to meet the performance, quality of service, and resource utilization requirements in a scalable manner are addressed. Open issues and research challenges for realizing the true potential of large-scale CASA networks are considered.
Keywords
adaptive signal processing; meteorological radar; sensor fusion; storms; weather forecasting; CASA network; NDN; cloud computing; collaborative adaptive sensing of the atmosphere; data pull mode; data streaming; data transport; hazardous weather phenomena detection; hazardous weather phenomena tracking; multisensor data fusion solution; named data networking; quality of service; radar data access; radar networking; resource utilization requirement; tornado; virtualization; weather radar; Data integration; Meteorological radar; Meteorology; Radar detection; Sensors; multi-sensor data fusion; named data; overlay networks; radar networks; streaming;
fLanguage
English
Publisher
ieee
Conference_Titel
Globecom Workshops (GC Wkshps), 2012 IEEE
Conference_Location
Anaheim, CA
Print_ISBN
978-1-4673-4942-0
Electronic_ISBN
978-1-4673-4940-6
Type
conf
DOI
10.1109/GLOCOMW.2012.6477784
Filename
6477784
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