TY - CHAP
T1 - Discrete quality assessment in IPTV content distribution networks
AU - Mu, Mu
AU - Mauthe, Andreas
AU - Haley, Robert
AU - Garcia, Francisco
PY - 2011/8
Y1 - 2011/8
N2 - Maintaining the quality of videos in resource-intensive IPTV services is challenging due to the nature of packet-based content distribution networks (CDN). Network impairments are unpredictable and highly detrimental to the quality of video content. Quality of the end user experience (QoE) has become a critical service differentiator. An efficient real-time quality assessment service in distribution networks is the foundation of service quality monitoring and management. The perceptual impact of individual impairments varies significantly and is influenced by complex impact factors. Without differentiating the impact of quality violation events to the user experience, existing assessment methodologies based on network QoS such as packet loss rate cannot provide adequate supports for the IPTV service assessment. A discrete perceptual impact evaluation quality assessment (DEQA) framework is introduced in this paper. The proposed framework enables a real-time, non-intrusive assessment service by efficiently recognising and assessing individual quality violation events in the IPTV distribution network. The discrete perceptual impacts to a media session are aggregated for the overall user level quality evaluation. With its deployment scheme the DEQA framework also facilitates efficient network diagnosis and QoE management. To realise the key assessment function of the framework and investigate the proposed advanced packet inspection mechanism, we also introduce the dedicated evaluation testbed - the LA2 system. A subjective experiment with data analysis is also presented to demonstrate the development of perceptual impact assessment functions using analytical inference, the tools of the LA2 system, subjective user tests and statistical modelling. © 2011 Elsevier B.V.
AB - Maintaining the quality of videos in resource-intensive IPTV services is challenging due to the nature of packet-based content distribution networks (CDN). Network impairments are unpredictable and highly detrimental to the quality of video content. Quality of the end user experience (QoE) has become a critical service differentiator. An efficient real-time quality assessment service in distribution networks is the foundation of service quality monitoring and management. The perceptual impact of individual impairments varies significantly and is influenced by complex impact factors. Without differentiating the impact of quality violation events to the user experience, existing assessment methodologies based on network QoS such as packet loss rate cannot provide adequate supports for the IPTV service assessment. A discrete perceptual impact evaluation quality assessment (DEQA) framework is introduced in this paper. The proposed framework enables a real-time, non-intrusive assessment service by efficiently recognising and assessing individual quality violation events in the IPTV distribution network. The discrete perceptual impacts to a media session are aggregated for the overall user level quality evaluation. With its deployment scheme the DEQA framework also facilitates efficient network diagnosis and QoE management. To realise the key assessment function of the framework and investigate the proposed advanced packet inspection mechanism, we also introduce the dedicated evaluation testbed - the LA2 system. A subjective experiment with data analysis is also presented to demonstrate the development of perceptual impact assessment functions using analytical inference, the tools of the LA2 system, subjective user tests and statistical modelling. © 2011 Elsevier B.V.
KW - Deep packet inspection
KW - IPTV
KW - Quality assessment
KW - Quality of experience
UR - http://www.mendeley.com/research/discrete-quality-assessment-iptv-content-distribution-networks
U2 - 10.1016/j.image.2011.03.002
DO - 10.1016/j.image.2011.03.002
M3 - Chapter
SN - 0923-5965
T3 - Signal Processing: Image Communication
SP - 339
EP - 357
BT - Signal Processing: Image Communication
ER -