首页> 外文会议>International Conference on E-health Networking, Application and Services >A hybrid quality evaluation approach based on fuzzy inference system for medical video streaming over small cell technology
【24h】

A hybrid quality evaluation approach based on fuzzy inference system for medical video streaming over small cell technology

机译:基于模糊推理系统对小型电池技术进行模糊推理系统的混合质量评价方法

获取原文

摘要

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.
机译:预计小型电池技术将成为未来5G网络的一个组成部分,以满足对交通量,频率效率和能量和成本降低的越来越高的用户需求。小型电池网络可以在提高M-Health应用程序中的服务质量(QoS)和经验质量(QoE)中发挥重要作用,特别是在医学视频流中。在本文中,我们提出了一种基于模糊推理系统(FIS)的混合医学QoE预测模型,其将网络QoS(NQOS)和应用QoS(AQOS)参数与QoE相关联。对小型电池技术的医学超声视频传输测试了该模型。结果表明,我们提出的模型的预测QoE评分与医学专家的主观评分具有高的相关性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号