Cloud Benchmarking For Maximising Performance of Scientific Applications
- Submitting institution
-
Queen's University of Belfast
- Unit of assessment
- 12 - Engineering
- Output identifier
- 135846491
- Type
- D - Journal article
- DOI
-
10.1109/TCC.2016.2603476
- Title of journal
- IEEE Transactions on Cloud Computing
- Article number
- -
- First page
- 170
- Volume
- 7
- Issue
- 1
- ISSN
- 2168-7161
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2016
- URL
-
-
- 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)
-
C - Electrical and Electronic
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Through combining important research streams of cloud computing and constraint programming a novel approach for benchmarking cloud resources to maximise application performance on any cloud platform was developed. This work resulted in an EPSRC Impact Acceleration Award EP/K503940/1that delivered a tool namely CloudBench to Takeda Pharmaceutical Company Ltd operating in the UK for selecting performance and cost efficient cloud resources for their research applications. The work has resulted in shaping cloud benchmarking research at universities in Lancaster, Zurich, Berlin and Gothenburg.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -