An Efficient Resource Management Mechanism for Network Slicing in a LTE Network
- Submitting institution
-
Liverpool John Moores University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 936
- Type
- D - Journal article
- DOI
-
10.1109/ACCESS.2019.2926446
- Title of journal
- IEEE Access
- Article number
- -
- First page
- 89441
- Volume
- 7
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- July
- 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
-
4
- Research group(s)
-
-
- Citation count
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work is the result of a research collaboration with the Korea Advanced Institute of Science and Technology (KAIST). The underpinning research, which led to the Best Paper (https://ieeexplore.ieee.org/document/7899423) awarded at ICIN 2017 sponsored by IEEE, was extended in this work to propose a novel network slicing resource management mechanism to satisfy user service requirements in an existing mobile network (LTE) as an urgent solution for efficient migration to 5G. The significant efforts to expand the work have been made whilst developing the international standardisation body ITU-T’s Recommendation Y.3156 on network slicing with AI-assisted analysis (Hu Yushuang, China Mobile, huyushuang@chinamobile.com).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
