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QoE-based Mobility-aware Collaborative Video Streaming on the Edge of 5G

Tuysuz, Mehmet Fatih; Aydin, Mehmet Emin

Authors

Mehmet Fatih Tuysuz

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Dr Mehmet Aydin Mehmet.Aydin@uwe.ac.uk
Senior Lecturer in Networks and Mobile Computing



Abstract

Today's Internet traffic is dominated by video streaming applications transmitted through wireless/cellular interfaces of mobile devices. Although ultra-high-definition videos are now easily transmitted through mobile devices, video quality level that users perceive is generally lower than expected due to distance-based high latency between sources and end-users. Mobile edge computing (MEC) paradigm is expected to address this issue and provide users with higher perceived Quality of Experience (QoE) for latency-critical applications, deploying MEC servers at edges. However, due to capacity concerns on MEC servers, a more comprehensive approach is needed to meet user's expectations applying all possible operations over the resources such as caching, pre-fetching and task offloading policies depending on the data repetition or memory/CPU utilization. To address these issues, this paper proposes a novel collaborative QoE-based mobility-aware video streaming scheme deployed at a MEC server. Throughout the paper, we demonstrate how the proposed scheme can be implemented so as to preserve the desired QoE level per user during entire video sessions. Performance of the proposed scheme has been investigated by extensive simulations. In comparison to existing schemes; the results illustrate that high efficiency is achieved through collaboration among MEC servers, utilizing explicit window size adaptation, collaborative pre-fetching and handover among the edges.

Journal Article Type Article
Journal IEEE Transactions on Industrial Informatics
Print ISSN 1551-3203
Electronic ISSN 1941-0050
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Pages 1-1
APA6 Citation Tuysuz, M. F., & Aydin, M. E. (in press). QoE-based Mobility-aware Collaborative Video Streaming on the Edge of 5G. IEEE Transactions on Industrial Informatics, 1-1. https://doi.org/10.1109/tii.2020.2972931
DOI https://doi.org/10.1109/tii.2020.2972931
Keywords Control and Systems Engineering; Electrical and Electronic Engineering; Information Systems; Computer Science Applications

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