Dynamic Bayesian Networks for Sequential Quality of Experience Modelling and Measurement

  • Karan Mitra
  • Arkady Zaslavsky
  • Christer Åhlund
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6869)


This paper presents a novel context-aware methodology for modelling and measuring user-perceived quality of experience (QoE) over time. In particular, we create a context-aware model for QoE modelling and measurement using dynamic Bayesian networks (DBN) and a context-aware state-space approach. The proposed model is then used to infer and determine users’ QoE in a sequential manner. We performed experimentation to validate the proposed model. The results prove that it can efficiently model, reason and measure QoE of the users’.


Algorithm Bayesian network dynamic Bayesian network context-awareness quality of experience quality of service 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Karan Mitra
    • 1
    • 2
  • Arkady Zaslavsky
    • 1
    • 2
  • Christer Åhlund
    • 2
  1. 1.Caulfield School of Information TechnologyMonash UniversityVictoriaAustralia
  2. 2.Luleå University of TechnologyLuleåSweden

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