network-based monitoring of quality of experience

Recent years have observed a tremendous shift from the technology-centric assessment to the user-centric assessment of network services. Obviously, a sustainable network management approach cares about the user demands and expectations. Consequently, the measurement and modeling of Quality of Experience (QoE) attracted many contributions from researchers and practitioners. Generally, QoE is assessed at two levels, i.e., Application and Network level. While the former usually allows QoE assessment on the test traffic with control on client-side instrumentation, the latter opens the avenues for continuous QoE assessment on the traffic generated by the real users. This thesis contributes towards passive network-level assessment of QoE. This thesis document begins with a background on the fundamentals of Network Management and objective QoE assessment. It extends the discussion further to the QoE-centric monitoring and management of network, complimented by the details about QoE estimator agent developed within the Celtic project QuEEN (Quality of Experience Estimators in Network). The discussion on findings start with results from subjective tests to understand the relationship between waiting times and user subjective feedback over time. These results help strengthen the understanding of timescales on which users react, as well as, the role of memory effect. The findings show that QoE drops significantly with delays on the timescales of 1–4 s. With recurring delays, the user tolerance to waiting times decreases constantly showing the signs of memory effect. Subsequently, this document introduces and evaluates a passive wavelet-