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Towards QoE Management

Towards QoE Management. Tobias Hoßfeld hossfeld@informatik.uni-wuerzburg.de. QoE Management. Access Network. Overlay Adaptation How to adapt the overlay? Self-Organization mechanisms?. Core Network. Understand QoE Different applications: file sharing, video on demand, live TV, etc.

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Towards QoE Management

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  1. Towards QoE Management Tobias Hoßfeldhossfeld@informatik.uni-wuerzburg.de

  2. QoE Management Access Network Overlay Adaptation How to adapt the overlay? Self-Organization mechanisms? Core Network Understand QoE Different applications: file sharing, video on demand, live TV, etc. Impact of various parameters? Application Server QoE Control Where to react? How to react? Within the network? At the edge? Access Network • Goal: • - maximize QoE • minimize costs QoE Monitoring Where to monitor? What to monitor? How to estimate QoE? End user

  3. Current work: Understanding QoE • IQX hypothesis: exponential interdependency between QoE and QoS parameter: QoE = f(QoS) • tested for voice, currently for other applications, can be used for QoE control • SmoothIt project: major influence factors on QoE for file sharing and video streaming • G-Lab project: extension toscalabe video codecs • QoEWeb project: Derive QoE and user behavior model for web traffic based on • active measurements in a laboratory test • passive measurements within an operator’s network

  4. 0.4 400 400 packet size Packet loss Packet sizes 0.2 200 200 packetloss 0 0 0 0 0 0 0.5 0.5 0.5 1 1 1 1.5 1.5 1.5 2 2 2 2.5 2.5 2.5 3 3 3 Time [ms] 6 6 6 x 10 x 10 x 10 Current work: QoE Control • G-Lab: QoE control of P2P VoD • by adapting the self-organization mechanisms • by using scalable video codec extension of H.264 • SmoothIt: Simple Economic Management Approaches of Overlay Traffic in Heterogeneous Internet Topologies • Overlay applications and requirements: QoE++ • Operator’s Point of View: Costs-- • Economic Traffic Management: combine QoE, Costs, Security through Incentives

  5. Quantification of QoE • … is difficult and depends on several factors • type of application and corresponding human perception • user’s expectations (and payments for a service) • user’s experience from the past (long-term and short-term) • offered contents / popularity of service • GUI and usability of application software • technical environment (user equipment, network access, etc) • … • Let the users decide! E.g. video streaming • long startup delay , but smooth video playout • short startup delay, but rough, jerky playout • user may adjust pre-buffering time  user will get used to it and adapts its expectations 

  6. Further Issues • Mean opinion scores are not enough! • Users have completely different opinions • Sensitivity of QoE has to be taken into account, which is higher for good QoE •  SOS = standard deviation of opinion scores • User, application and network have to communicate! Integrate feedback from the users? • Monitoring of QoE • How to assess QoE within the network on the example of P2P VoD? QoE ≠ ∑ QoSi • Can we use sampling techniques for assessing QoE?

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