Improving Quality of Experience in multimedia Internet of Things leveraging machine learning on big data

• Main Authors: Huang, Xiaohong, Xie, Kun, Leng, Supeng, Yuan, Tingting, Ma, Maode
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Data Fusion; Multimedia Internet of Things
• Online Access: https://hdl.handle.net/10356/141162
• Institution: Nanyang Technological University

With rapid evolution of the Internet of Things (IoT) applications on multimedia, there is an urgent need to enhance the satisfaction level of Multimedia IoT (MIoT) network users. An important and unsolved problem is automatic optimization of Quality of Experience (QoE) through collecting/managing/processing various data from MIoT network. In this paper, we propose an MIoT QoE optimization mechanism leveraging data fusion technology, called QoE optimization via Data Fusion (QoEDF). QoEDF consists of two steps. Firstly, a multimodal data fusion approach is proposed to build a QoE mapping between the uncontrollable user data with the controllable network-related system data. Secondly, an automatic QoE optimization model is built taking fused results, which is different from the traditional way. QoEDF is able to adjust network-related system data automatically so as to achieve optimized user satisfaction. Simulation results show that QoEDF will lead to significant improvements in QoE level as well as be adaptable to dynamic network changes.