Architecting Time-Critical Big-Data Systems

Pablo Basanta-Val, Neil Cameron Audsley, Andrew John Wellings, Ian Gray, Norberto Fernandez-Garcio

Research output: Contribution to journalArticlepeer-review


Current infrastructures for developing big-data applications are able to process –via big-data analytics- huge amounts of data, using clusters of machines that collaborate to perform parallel computations. However, current infrastructures were not designed to work with the requirements of time-critical applications; they are more focused on general-purpose applications rather than time-critical ones. Addressing this issue from the perspective of the real-time systems community, this paper considers time-critical big-data. It deals with the definition of a time-critical big-data system from the point of view of requirements, analyzing the specific characteristics of some popular big-data applications. This analysis is complemented by the challenges stemmed from the infrastructures that support the applications, proposing an architecture and offering initial performance patterns that connect application costs with infrastructure performance.
Original languageEnglish
Pages (from-to)310-324
JournalIEEE Transactions on Big Data
Issue number4
Early online date31 Oct 2016
Publication statusE-pub ahead of print - 31 Oct 2016

Bibliographical note

© IEEE, 2016. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details


  • time-critical infrastructure, time-critical, big-data systems

Cite this