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Title: Parametric assessment of video quality in content distribution networks
Author: Mu , Mu
Awarding Body: Lancaster University
Current Institution: Lancaster University
Date of Award: 2011
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IP-based packet-switched networks have become one of the main content distribution platforms for emerging multimedia services such as IPTV, thanks to the rapidly growing bandwidth and exclusive internetworking and interactivity features of IP-based networks. Meanwhile, high quality video content services are becoming particularly popular within content delivery networks (CDN). During content distribution, packets of encoded video streams can be delayed, corrupted or dropped due to network impairments in packet-switched networks. This leads to perceptual quality degradations of the delivered content at receiver. Although network impairments are rare in commercial managed networks, any distortion caused by impairments can be highly detrimental to end users' experience. Consequently the ability to meet customer expectations on video quality has become a critical service differentiator. Quality of Experience (QoE) that was merely recognised as a value-added service of traditional content distribution services is now one of the fundamental requirements and challenges of providing high quality video services. In order to maintain a high level of user experience throughout the life-cycle of a video service, a service quality measurement and management service must be established. In this thesis a parametric assessment model is designed and implemented to provide accurate in-service quality assessment services with respect to human users' perception of visual distortions. The model monitors video quality specifically in response to discrete network impairment events. Multiple impact factors and quantification metrics have been defined for the realisation of assessment functions. Exploiting specifically designed discrete analysis methodology and packet inspection mechanisms, the designed assessment model aims at supporting a quality monitoring service in large scale commercial video content networks. A testbed system, the LA2 system, is also developed to provide an assortment of tools for the design and evaluation of parametric assessment models. Using the LA2 system, comprehensive test plans and subjective experiments are specified and conducted to establish relevant impact factors and to quantitatively model users' opinion of visual distortions as a set of assessment functions. Specifically, the statistical binary logistic model and cumulative logit model are employed to model the distribution of perceivability of content loss distortion in dichotomous and polytomous scales. The designed model provides high performance estimations to subjective user opinions according to selected statistical fitness tests. A validation test also verifies the generality of the designed model
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available