TITLE:
Recommendations for Big Data in Online Video Quality of Experience Assessment
AUTHORS:
Ethan Court, Kapilan Radhakrishnan, Kemi Ademoye, Stephen Hole
KEYWORDS:
Quality of Experience, QoE, Big Data, Online, Video, Traffic
JOURNAL NAME:
Journal of Computer and Communications,
Vol.4 No.5,
May
26,
2016
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.