%0 Conference Paper %1 info3-inproceedings-2012-437 %A Schatz, Raimund %A Hoßfeld, Tobias %A Casas, Pedro %B Best Paper Award at Workshop on Future Internet and Next Generation Networks (FINGNet-2012) %C Palermo, Italy %D 2012 %K myown demobenefit vnf_qoe_cloud %T Passive YouTube QoE Monitoring for ISPs %X Over last decade, Quality of Experience (QoE) has become the guiding paradigm for enabling a more usercentric understanding of quality of communication networks and services. The intensifying competition among ISPs and the exponentially increasing traffic volumes caused by online video platforms like YouTube is forcing service providers to integrate QoE into their corporate DNA. This paper investigates the problem of YouTube QoE monitoring from an access provider’s perspective. To this end, we present three novel methods for in-network measurement of the QoE impairment that dominates user perception in the context of HTTP video-streaming: stalling of playback. Our evaluation results show that it is possible to detect applicationlevel stalling events at high accuracy by using network-level passive probing only. However, only the most complex and most accurate approach can be used for QoE prediction due to the non-linearities inherent in human quality perception.

@inproceedings{info3-inproceedings-2012-437, abstract = {Over last decade, Quality of Experience (QoE) has become the guiding paradigm for enabling a more usercentric understanding of quality of communication networks and services. The intensifying competition among ISPs and the exponentially increasing traffic volumes caused by online video platforms like YouTube is forcing service providers to integrate QoE into their corporate DNA. This paper investigates the problem of YouTube QoE monitoring from an access provider’s perspective. To this end, we present three novel methods for in-network measurement of the QoE impairment that dominates user perception in the context of HTTP video-streaming: stalling of playback. Our evaluation results show that it is possible to detect applicationlevel stalling events at high accuracy by using network-level passive probing only. However, only the most complex and most accurate approach can be used for QoE prediction due to the non-linearities inherent in human quality perception.}, added-at = {2016-03-10T17:37:58.000+0100}, address = {Palermo, Italy}, author = {Schatz, Raimund and Hoßfeld, Tobias and Casas, Pedro}, biburl = {https://www.bibsonomy.org/bibtex/2fa5cfe3c933a95cd1a1b43529f4a8533/uniwue_info3}, booktitle = {Best Paper Award at Workshop on Future Internet and Next Generation Networks (FINGNet-2012)}, interhash = {4eb56eecea3bcb0e2d0e1fa18e1c500a}, intrahash = {fa5cfe3c933a95cd1a1b43529f4a8533}, keywords = {myown demobenefit vnf_qoe_cloud}, month = {7}, timestamp = {2022-03-14T00:10:52.000+0100}, title = {Passive YouTube QoE Monitoring for ISPs}, year = 2012 }