ControCity: An Autonomous Approach for Controlling Elasticity Using Buffer Management in Cloud Computing Environment
- Submitting institution
-
Liverpool John Moores University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1582
- Type
- D - Journal article
- DOI
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10.1109/ACCESS.2019.2932462
- Title of journal
- IEEE Access
- Article number
- -
- First page
- 106912
- Volume
- 7
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2019
- 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
-
3
- Research group(s)
-
-
- Citation count
- 14
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work resulted from an international collaboration with researchers at Islamic Azad University in Iran. Its main contribution includes an autonomous framework for cloud elasticity management supported by a learning automata technique for smart decision-making. The experiments conducted show the performance gain of the framework over related approaches. In particular, it can increase resource utilisation by up to 8.4%, which is beneficial to cloud providers.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
