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Rehman, Ikram 
ORCID: https://orcid.org/0000-0003-0115-9024, Philip, Nada and Nasralla, Moustafa M.
(2016)
A hybrid quality evaluation approach based on fuzzy inference system for medical video streaming over small cell technology.
In: 18th International Conference on e-Health, Networking, Application and Services (IEEE - HealthCom), 14-16 Sept 2016, Munich, Germany.
Abstract
Small cell technology is expected to be an integral part of future 5G networks in order to meet the increasingly high user demands for traffic volume, frequency efficiency, and energy and cost reductions. Small cell networks can play an important role in enhancing the Quality of Service (QoS) and Quality of Experience (QoE) in m-health applications, and in particular, in medical video streaming. In this paper, we propose a hybrid medical QoE prediction model based on a Fuzzy Inference System (FIS) that correlates the network QoS (NQoS) and application QoS (AQoS) parameters to the QoE. The model is tested on the transmission of medical ultrasound video over small cell technology. The results show that the predicted QoE scores of our proposed model have a high correlation with the subjective scores of medical experts.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| ISBN: | 9781509033706 |
| Identifier: | 10.1109/HealthCom.2016.7749485 |
| Page Range: | pp. 1-6 |
| Identifier: | 10.1109/HealthCom.2016.7749485 |
| Additional Information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Keywords: | small cells, m-health, fuzzy logic, QoS, QoE, 5G, medical video streaming |
| Subjects: | Computing |
| Depositing User: | Ikram Rehman |
| Date Deposited: | 10 Jul 2019 09:25 |
| Last Modified: | 28 Aug 2021 07:11 |
| URI: | https://repository.uwl.ac.uk/id/eprint/6234 |
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