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
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;
Conference_Titel :
Aerospace Conference, 2012 IEEE
Conference_Location :
Big Sky, MT
Print_ISBN :
978-1-4577-0556-4
DOI :
10.1109/AERO.2012.6187090