Large-scale real-time data-driven scientific applications

  • Junwei Cao*
  • , Junwei Li
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Large-scale real-time data processing is becoming common in many scientific disciplines. But processing large amount of data in real-time is still challenging with existing technology. In last few years, the dynamic data driven approach is becoming people's spotlight due to its potential in reducing data intelligently. Enlighten by this concept, a new data-driven framework for large-scale real-time data analysis is proposed in this work and a scientific application under this framework is given in details. By introducing additional information to data analysis processes, large-scale data processing can be achieved with real-time time constraint.

Original languageEnglish
Title of host publicationProceedings - 2nd International Conference on Networking and Distributed Computing, ICNDC 2011
Pages116-121
Number of pages6
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2nd International Conference on Networking and Distributed Computing, ICNDC 2011 - Beijing, China
Duration: 21 Sept 201124 Sept 2011

Publication series

NameProceedings - 2nd International Conference on Networking and Distributed Computing, ICNDC 2011

Conference

Conference2nd International Conference on Networking and Distributed Computing, ICNDC 2011
Country/TerritoryChina
CityBeijing
Period21/09/1124/09/11

Keywords

  • Dynamic data-driven
  • Real-time computing
  • Scalability
  • Scientific applications

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