A reference architecture for big data systems

Authors: Sang, G.M., Xu, L. and De Vrieze, P.

http://eprints.bournemouth.ac.uk/30020/

Start date: 15 December 2016

Pages: 370-375

This data was imported from Scopus:

Authors: Sang, G.M., Xu, L. and De Vrieze, P.

http://eprints.bournemouth.ac.uk/30020/

Journal: SKIMA 2016 - 2016 10th International Conference on Software, Knowledge, Information Management and Applications

Pages: 370-375

ISBN: 9781509032976

DOI: 10.1109/SKIMA.2016.7916249

© 2016 IEEE. Over dozens of years, applying new IT technologies into organizations has always been a big concern for business. Big data certainly is a new concept exciting business. To be able to access more data and empower to analysis big data requires new big data platforms. However, there still remains limited reference architecture for big data systems. In this paper, based on existing reference architecture of big data systems, we propose new high level abstract reference architecture and related reference architecture notations, that better express the overall architecture. The new reference architecture is verified using one existing case and an additional new use case.

This data was imported from Web of Science (Lite):

Authors: Sang, G.M., Xu, L. and de Vrieze, P.

http://eprints.bournemouth.ac.uk/30020/

Journal: PROCEEDINGS OF 2016 10TH INTERNATIONAL CONFERENCE ON SOFTWARE, KNOWLEDGE, INFORMATION MANAGEMENT & APPLICATIONS (SKIMA)

Pages: 370-375

ISSN: 2373-082X

The data on this page was last updated at 05:13 on February 22, 2020.