Green scheduling, flows and matchings
- Submitting institution
-
King's College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 139537826
- Type
- D - Journal article
- DOI
-
10.1016/j.tcs.2015.02.020
- Title of journal
- Theoretical Computer Science
- Article number
- -
- First page
- 126
- Volume
- 579
- Issue
- -
- ISSN
- 0304-3975
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2015
- 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
-
2
- Research group(s)
-
-
- Citation count
- 11
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work develops a method to design and analyse optimal algorithms for CPU energy allocation problems based on network flow and matching techniques that exploit the energy continuity and nonlinearity. Using this method, optimal algorithms for three fundamental speed scaling problems were derived, which allow saving energy in computer systems by properly varying the processing execution speed (frequency). Subsequent works have extended these network flow ideas to obtain faster algorithms (e.g. Shioura et al. INFORMS J. Comp. 2017) and to incorporate more complex rigid, parallel resource constraints (e.g. Kononov et al. Journal of Scheduling 2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -