Recommendations for Big Data in Online Video Quality of Experience Assessment

HTML  XML Download Download as PDF (Size: 391KB)  PP. 24-31  
DOI: 10.4236/jcc.2016.45004    1,866 Downloads   2,849 Views  

ABSTRACT

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.

Share and Cite:

Court, E. , Radhakrishnan, K. , Ademoye, K. and Hole, S. (2016) Recommendations for Big Data in Online Video Quality of Experience Assessment. Journal of Computer and Communications, 4, 24-31. doi: 10.4236/jcc.2016.45004.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.