Holistic Virtual Machine Scheduling in Cloud Datacenters towards Minimizing Total Energy
- Submitting institution
-
The University of Leeds
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- UOA11-1587
- Type
- D - Journal article
- DOI
-
10.1109/TPDS.2017.2688445
- Title of journal
- IEEE Transactions on Parallel and Distributed Systems
- Article number
- -
- First page
- 1317
- Volume
- 29
- Issue
- 6
- ISSN
- 1045-9219
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2017
- 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)
-
E - DSS (Distributed Systems and Services)
- Citation count
- 25
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Data centres are the fundamental infrastructure on which all modern distributed systems (Clouds, IoT) are based, consuming over 3% of the global electrical supply but are extremely inefficient – typically running at 10-15% utilization. Primary energy consumption of a data centre consists of computing energy and cooling energy, often quantified separately, leading to unrealistic assumptions and solutions. This paper presents an approach for optimising the total energy saving, which controls operational and thermal energy consumptions within a unified framework. The approach was validated using Google tracelog. Clear impact for cloud service and infrastructure providers (Edgetic paul.townend@edgetic.com, RISE-SICS jon.summers@ri.se, Techbuyer R.Kenny@techbuyer.com).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
