An Approach to Optimise Resource Provision with Energy-awareness in Datacentres by Combating Task Heterogeneity
- Submitting institution
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The University of Leicester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1437
- Type
- D - Journal article
- DOI
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10.1109/tetc.2018.2794328
- Title of journal
- IEEE Transactions on Emerging Topics in Computing
- Article number
- -
- First page
- 762
- Volume
- 8
- Issue
- 3
- ISSN
- 2168-6750
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2018
- URL
-
-
- Supplementary information
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https://doi.org/10.1109/TETC.2018.2794328
- 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
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2
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Cloud datacentres are now massive energy consumers and key environmental polluters. This paper presents a significant research work to optimise the level of resource provisioning through workload data analytics in order to reduce energy consumption of data centres incurred in the form of idle resource proportions during task execution. The preliminary model presented in IEEE International Conference on Data Science and Systems (IEEE DSS 2018), has received the Best Paper Award from this reputable IEEE conference in the area of data science. The thesis reporting this research work was nominated to the British Computer Society (BCS)’s Best PhD Thesis Award.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -