QoE-based mobility-aware collaborative video streaming on the edge of 5G

Tuysuz, Mehmet Fatih; Aydin, Mehmet Emin

Abstract

Today's Internet traffic is dominated by video streaming applications transmitted through wireless/cellular interfaces of mobile devices. Although ultrahigh-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 users' expectations applying all possible operations over the resources such as caching, prefetching, and task offloading policies depending on the data repetition or memory/CPU utilization. To address these issues, this article proposes a novel collaborative QoE-based mobility-aware video streaming scheme deployed at MEC servers. Throughout the article, 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 prefetching, and handover among the edges.

• Journal Article Type: Article
• Acceptance Date: Jan 26, 2020
• Online Publication Date: Feb 10, 2020
• Publication Date: Nov 1, 2020
• Deposit Date: Feb 11, 2020
• Publicly Available Date: Feb 13, 2020
• Journal: IEEE Transactions on Industrial Informatics
• Print ISSN: 1551-3203
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 16
• Issue: 11
• Pages: 7115-7125
• DOI: https://doi.org/10.1109/tii.2020.2972931
• Keywords: Control and Systems Engineering; Electrical and Electronic Engineering; Information Systems; Computer Science Applications
• Public URL: https://uwe-repository.worktribe.com/output/5369631