QoE-aware QoS management

F. Agboma, A. Liotta

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

71 Citations (Scopus)
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Abstract

The streaming of multimedia contents (e.g., Mobile TV) is a bandwidth intensive service. The network operator's aim is to provide an acceptable user experience at minimal network resource usage. It is important from the network operator's perspective to be aware of: 1) the thresholds at which the user's perception of service quality becomes unacceptable; and 2) the degree of influence of each of the Quality of Service (QoS) parameters on the user perception. However, very little is known about the formal methods to optimize the use of QoS mechanisms in relation to the user's Quality of Experience (QoE). In this paper, we explain how the user's QoE can be captured. A statistical modelling technique is employed which, correlates QoS parameters with estimates of QoE perceptions and identifies the degree of influence of each QoS parameters on the user perception. The network operator can apply this information to efficiently, and accurately undertake network dimensioning and service provisioning strategies. This proposed methodology is applied to demonstrate QoE management strategies, thus paving the way towards QoE-aware QoS management.
Original languageEnglish
Title of host publicationMoMM'2008 (The 6th International Conference on Advances in Mobile Computing and Multimedia, Linz, Austria, November 24-26, 2008. Proceedings)
EditorsG. Kotsis, D. Taniar, E. Pardede, I.K. Ibrahim
Place of PublicationNew York NY
PublisherAssociation for Computing Machinery, Inc
Pages111-116
ISBN (Print)978-1-60558-269-6
DOIs
Publication statusPublished - 2008

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    Agboma, F., & Liotta, A. (2008). QoE-aware QoS management. In G. Kotsis, D. Taniar, E. Pardede, & I. K. Ibrahim (Eds.), MoMM'2008 (The 6th International Conference on Advances in Mobile Computing and Multimedia, Linz, Austria, November 24-26, 2008. Proceedings) (pp. 111-116). Association for Computing Machinery, Inc. https://doi.org/10.1145/1497185.1497210