Privacy-Aware Scheduling SaaS in High Performance Computing Environments
- Submitting institution
-
University of Newcastle upon Tyne
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 227435-70661-1292
- Type
- D - Journal article
- DOI
-
10.1109/TPDS.2016.2603153
- Title of journal
- IEEE Transactions on Parallel and Distributed Systems
- Article number
- -
- First page
- 1176
- Volume
- 28
- Issue
- 4
- ISSN
- 1045-9219
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2016
- URL
-
http://dx.doi.org/10.1109/TPDS.2016.2603153
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
D - Scalable Computing
- Citation count
- 10
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper was the result of a collaboration with one of the world’s leading scheduling groups (at the University of Sydney). Its novelty is in combining their work with the result of 5 years work at Newcastle on Cloud Security in order to create a novel method that reduces the cost of executing workflows while satisfying both privacy and deadline constraints.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -