An incremental approach for real-time Big Data visual analytics

Authors: García, I., Casado, R., García, V. and Bouchachia, A.

http://eprints.bournemouth.ac.uk/27237/

Start date: 22 August 2016

This data was imported from Scopus:

Authors: Garcia, I., Casado, R. and Bouchachia, A.

http://eprints.bournemouth.ac.uk/27237/

Journal: Proceedings - 2016 4th International Conference on Future Internet of Things and Cloud Workshops, W-FiCloud 2016

Pages: 177-182

ISBN: 9781509039463

DOI: 10.1109/W-FiCloud.2016.46

© 2016 IEEE. In the age of Big Data, the real-Time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-Time visualization of extremely large data-At-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-Time.

This source preferred by Hamid Bouchachia

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

Authors: Garcia, I., Casado, R. and Bouchachia, A.

http://eprints.bournemouth.ac.uk/27237/

Journal: 2016 IEEE 4TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (FICLOUDW)

Pages: 177-182

DOI: 10.1109/W-FiCloud.2016.46

The data on this page was last updated at 04:40 on November 22, 2017.