Outputs (119)

Video quality degradation on IPTV networks (2012)
Presentation / Conference Contribution
Okyere-Benya, J., Aldiabat, M., Menkovski, V., Exarchakos, G., & Liotta, A. (2012). Video quality degradation on IPTV networks. . https://doi.org/10.1109/ICCNC.2012.6167513

In IPTV streaming, issues of entire frame losses limit the use of state-of-the-art video quality analyses techniques. We present an experimental evaluation of degradation in video quality when streaming different types of video in an IPTV scenario. T... Read More about Video quality degradation on IPTV networks.

Adaptive psychometric scaling for video quality assessment (2012)
Journal Article
Menkovski, V., & Liotta, A. (2012). Adaptive psychometric scaling for video quality assessment. Signal Processing: Image Communication, 27(8), 788-799. https://doi.org/10.1016/j.image.2012.01.004

Video quality estimation is crucial for the efficient management of video delivery services. Particularly with the advances in screen technology and content delivery networks, getting an accurate estimation of the video quality as it is actually perc... Read More about Adaptive psychometric scaling for video quality assessment.

Privacy in Pervasive Systems: Legal Framework and Regulatory Challenges (2011)
Book Chapter
Liotta, A., & Liotta, A. (2011). Privacy in Pervasive Systems: Legal Framework and Regulatory Challenges. In Pervasive Computing and Communications Design and Deployment: Technologies, Trends and Applications (263-277). IGI Global. https://doi.org/10.401

Data protection legislation has developed in a digital communication context that is changing dramatically. Infrastructure-based, networked systems are increasingly interconnecting and interoperating with infrastructure-less or even spontaneous netwo... Read More about Privacy in Pervasive Systems: Legal Framework and Regulatory Challenges.

Networks for Pervasive Services: Six Ways to Upgrade the Internet (2011)
Book
Liotta, A., & Exarchakos, G. (2011). Networks for Pervasive Services: Six Ways to Upgrade the Internet. Springer. https://doi.org/10.1007/978-94-007-1473-1

Since its inception in the 1970s the Internet has become larger, faster and wireless. It is the biggest machine ever built, the “generative” engine of our digital society. However, the software that runs the global network has not seen any substantia... Read More about Networks for Pervasive Services: Six Ways to Upgrade the Internet.

Can Skype be used beyond video calling? (2011)
Presentation / Conference Contribution
Exarchakos, G., Menkovski, V., & Liotta, A. (2011). Can Skype be used beyond video calling?. In Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia (155-161). https://doi.org/10.1145/2095697.2095725

Skype nodes generate a substantial part of real-time bi-directional video traffic nowadays. Employing a range of adaptive mechanisms, the application configures video streaming to meet the requirements of the communication and constraints of the unde... Read More about Can Skype be used beyond video calling?.

The value of relative quality in video delivery (2011)
Journal Article
Menkovski, V., Exarchakos, G., & Liotta, A. (2011). The value of relative quality in video delivery. Journal of Mobile Multimedia, 7(3), 151-162

Estimating perceived quality of video is typically done by gauging the user's response on an absolute scale of ratings (excellent, good, fair, poor and bad). However, the internal representation of these adjectives to the stimuli varies significantly... Read More about The value of relative quality in video delivery.

Machine Learning approach for Quality of Experience aware networks (2010)
Presentation / Conference Contribution
Menkovski, V., Exarchakos, G., & Liotta, A. (2010). Machine Learning approach for Quality of Experience aware networks. . https://doi.org/10.1109/INCOS.2010.86

Efficient management of multimedia services necessitates the understanding of how the quality of these services is perceived by the users. Estimation of the perceived quality or Quality of Experience (QoE) of the service is a challenging process due... Read More about Machine Learning approach for Quality of Experience aware networks.

Localized Multistreams for P2P Streaming (2010)
Journal Article
Alhaisoni, U. O. E., Ghanbari, M., & Liotta, A. (2010). Localized Multistreams for P2P Streaming. International Journal of Digital Multimedia Broadcasting, 2010, Article 843574. https://doi.org/10.1155/2010/843574

Streaming video over the Internet, including cellular networks, has now become a commonplace. Network operators typically use multicasting or variants of multiple unicasting to deliver streams to the user terminal in a controlled fashion. P2P streami... Read More about Localized Multistreams for P2P Streaming.

Quality of experience models for multimedia streaming (2010)
Journal Article
Liotta, A., Menkovski, V., Exarchakos, G., & Sánchez, A. (2010). Quality of experience models for multimedia streaming. International Journal of Mobile Computing and Multimedia Communications, 2(4), 1-20. https://doi.org/10.4018/jmcmc.2010100101

Understanding how quality is perceived by viewers of multimedia streaming services is essential for efficient management of those services. Quality of Experience QoE is a subjective metric that quantifies the perceived quality, which is crucial in th... Read More about Quality of experience models for multimedia streaming.

Estimations and remedies for Quality of Experience in multimedia streaming (2010)
Presentation / Conference Contribution
Menkovski, V., Exarchakos, G., Liotta, A., & Sánchez, A. (2010). Estimations and remedies for Quality of Experience in multimedia streaming. . https://doi.org/10.1109/CENTRIC.2010.14

Managing multimedia network services in a User-centric manner provides for more delivered quality to the users, whilst maintaining a limited footprint on the network resources. For efficient User-centric management it is imperative to have a precise... Read More about Estimations and remedies for Quality of Experience in multimedia streaming.