Basanta-Val, Pablo, Audsley, Neil Cameron orcid.org/0000-0003-3739-6590, Wellings, Andrew John orcid.org/0000-0002-3338-0623 et al. (2 more authors) (2016) Architecting Time-Critical Big-Data Systems. IEEE Transactions on Big Data. pp. 310-324. ISSN 2332-7790
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 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 |
Keywords: | time-critical infrastructure, time-critical, big-data systems |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 07 Dec 2016 09:44 |
Last Modified: | 23 Jan 2025 00:09 |
Published Version: | https://doi.org/10.1109/TBDATA.2016.2622719 |
Status: | Published online |
Refereed: | Yes |
Identification Number: | 10.1109/TBDATA.2016.2622719 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:109070 |
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