Multimedia traffic quality of service management using statistical and artificial intelligence techniques
- Submitting institution
-
Sheffield Hallam University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1388
- Type
- D - Journal article
- DOI
-
10.1049/iet-cds.2013.0454
- Title of journal
- IET Circuits, Devices & Systems
- Article number
- 5
- First page
- 367
- Volume
- 8
- Issue
- 5
- ISSN
- 1751-858X
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- 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
-
1
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper brings together statistical and artificial intelligence method in order to assess quality of service in computer networks. The work was presented in a number of international research conferences. It was part of a completed PhD study. The PhD student involved is now Deputy for Scientific Affairs, Faculty of Information Technology, Alzintan University, Libya. The developed computer network technology assisted improved communication in medical devices and helped us to secure £15,000 Advanced Wellbeing Research Centre - Sheffield Hallam University fund that is devising a wireless respiratory monitor for monitoring and diagnosing apnoea.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -