Adaptive resource management and control in software defined networks
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2397
- Type
- D - Journal article
- DOI
-
10.1109/TNSM.2015.2402752
- Title of journal
- IEEE Transactions on Network and Service Management
- Article number
- -
- First page
- 18
- Volume
- 12
- Issue
- 1
- ISSN
- 1932-4537
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
10.1109/TNSM.2015.2402752
- 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
- 62
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- We demonstrate how a network management system design based on software-defined networking principles facilitates adaptive resource management and control. This work led to a new collaboration with the Department of Engineering, University of Perugia, Italy, that produced two publications (IEEE TNSM 2017 Transactions; https://ieeexplore.ieee.org/abstract/document/7968479 and IEEE/IFIP NOMS 2016 (acceptance rate: 25.3%/213); https://ieeexplore.ieee.org/abstract/document/7502808). The results were presented to the Sky UK network operations team (2017), Huawei (2018) and Ericsson/Telefonica at the Workshop on Network Function Virtualization and Programmable Networks at EUCNC 2015 (https://www.eucnc.eu/2015/www.eucnc.eu/indexa069.html?q=node/113). The work contributed to Tuncer’s Imperial College Research Fellowship in 2018.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
