DocumentCode
1880454
Title
Big data challenges for large radio arrays
Author
Jones, Dayton L. ; Wagstaff, Kiri ; Thompson, David R. ; Addario, Larry D. ; Navarro, Robert ; Mattmann, Chris ; Majid, Walid ; Lazio, Joseph ; Preston, Robert ; Rebbapragada, Umaa
Author_Institution
Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
fYear
2012
fDate
3-10 March 2012
Firstpage
1
Lastpage
6
Abstract
Future large radio astronomy arrays, particularly the Square Kilometre Array (SKA), will be able to generate data at rates far higher than can be analyzed or stored affordably with current practices. This is, by definition, a "big data" problem, and requires an end-to-end solution if future radio arrays are to reach their full scientific potential. Similar data processing, transport, storage, and management challenges face next-generation facilities in many other fields. The Jet Propulsion Laboratory is developing technologies to address big data issues, with an emphasis in three areas: 1) Lower-power digital processing architectures to make highvolume data generation operationally affordable, 2) Date-adaptive machine learning algorithms for real-time analysis (or "data triage") of large data volumes, and 3) Scalable data archive systems that allow efficient data mining and remote user code to run locally where the data are stored.
Keywords
radioastronomy; radiotelescopes; Square Kilometre Array; big data problem; data processing; end-to-end solution; jet propulsion laboratory; large radio astronomy arrays; lower-power digital processing architectures; next-generation facilities; storage; transport; Antennas; Arrays; Data handling; Data storage systems; Information management; Radio astronomy; Transient analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Aerospace Conference, 2012 IEEE
Conference_Location
Big Sky, MT
ISSN
1095-323X
Print_ISBN
978-1-4577-0556-4
Type
conf
DOI
10.1109/AERO.2012.6187090
Filename
6187090
Link To Document