UMTS Networks: Architecture, Mobility and Services
UMTS Networks: Architecture, Mobility and Services
A comparison of mechanisms for improving mobile IP handoff latency for end-to-end TCP
Proceedings of the 9th annual international conference on Mobile computing and networking
Means and Methods for Collecting and Analyzing QoE Measurements in Wireless Networks
WOWMOM '06 Proceedings of the 2006 International Symposium on on World of Wireless, Mobile and Multimedia Networks
Quantifying Skype user satisfaction
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
GUI testing using computer vision
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Objective perceptual video quality measurement method based on hybrid no reference framework
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
An approach to modeling and control of QoE in next generation networks
IEEE Communications Magazine
Proceedings of the 6th International COnference
TOP: Tail Optimization Protocol For Cellular Radio Resource Allocation
ICNP '10 Proceedings of the The 18th IEEE International Conference on Network Protocols
Over the top video: the gorilla in cellular networks
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Q-score: proactive service quality assessment in a large IPTV system
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Identifying diverse usage behaviors of smartphone apps
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Passive YouTube QoE Monitoring for ISPs
IMIS '12 Proceedings of the 2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing
A quest for an Internet video quality-of-experience metric
Proceedings of the 11th ACM Workshop on Hot Topics in Networks
Video stream quality impacts viewer behavior: inferring causality using quasi-experimental designs
Proceedings of the 2012 ACM conference on Internet measurement conference
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Cellular network operators are now expected to maintain a good Quality of Experience (QoE) for many services beyond circuit-switched voice and messaging. However, new smart-phone "app" services, such as Over The Top (OTT) video delivery, are not under an operator's control. Furthermore, complex interactions between network protocol layers make it challenging for operators to understand how network-level parameters (e.g., inactivity timers, handover thresholds, middle boxes) will influence a specific app's QoE. This paper takes a first step to address these challenges by presenting a novel approach to estimate app QoE using passive network measurements. Our approach uses machine learning to obtain a function that relates passive measurements to an app's QoE. In contrast to previous approaches, our approach does not require any control over app services or domain knowledge about how an app's network traffic relates to QoE. We implemented our approach in Prometheus, a prototype system in a large U.S. cellular operator. We show with anonymous data that Prometheus can measure the QoE of real video-on-demand and VoIP apps with over 80% accuracy, which is close to or exceeds the accuracy of approaches suggested by domain experts.