Recommendations for Big Data in Online Video Quality of Experience Assessment

作     者：Ethan Court Kapilan Radhakrishnan Kemi Ademoye Stephen Hole Ethan Court;Kapilan Radhakrishnan;Kemi Ademoye;Stephen Hole

作者机构：School of Applied Computing (SOAC) University of Wales Trinity Saint David Swansea UK 

出 版 物：《Journal of Computer and Communications》 (电脑和通信（英文）)

年 卷 期：2016年第4卷第5期

页      面：24-31页

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：Quality of Experience QoE Big Data Online Video Traffic 

摘      要：Real-time video application usage is increasing rapidly. Hence, accurate and efficient assessment of video Quality of Experience (QoE) is a crucial concern for end-users and communication service providers. After considering the relevant literature on QoS, QoE and characteristics of video trans-missions, this paper investigates the role of big data in video QoE assessment. The impact of QoS parameters on video QoE are established based on test-bed experiments. Essentially big data is employed as a method to establish a sensible mapping between network QoS parameters and the resulting video QoE. Ultimately, based on the outcome of experiments, recommendations/re- quirements are made for a Big Data-driven QoE model.