An Analysis of Failure-Related Energy Waste in a Large-Scale Cloud Environment
- Submitting institution
-
The University of Leeds
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- UOA11-1586
- Type
- D - Journal article
- DOI
-
10.1109/TETC.2014.2304500
- Title of journal
- IEEE Transactions on Emerging Topics in Computing
- Article number
- -
- First page
- 166
- Volume
- 2
- Issue
- 2
- ISSN
- 2168-6750
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2014
- 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)
-
E - DSS (Distributed Systems and Services)
- Citation count
- 29
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Cloud providers are under great pressure to reduce operational costs while providing reliable services. Previously, the relationship between failures and system energy waste was unknown, and the state-of-the-art energy-efficient mechanisms relied on theoretical assumptions. This paper is the first work globally to quantify the impact of failures on energy waste within a real large-scale data centre consisting of 12,500 servers. Results provide key insight into understanding and identifying conditions where energy waste is produced. International impact includes keynote addresses (e.g. IEEE ISADS 2017) and new collaborations (Alibaba, Adapt). Commercialisation includes 2 patents, and Edgetic-spinout (2018, 2.5M+ investment/awards; Paul Townend paul.townend@edgetic.com).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
