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Innovative algorithms for prioritised AR/VR content delivery

Silva, Fabio orcid logoORCID: 0000-0001-6019-372X, Bogusevschi, Diana and Muntean, Gabriel-Miro orcid logoORCID: 0000-0002-9332-4770 (2018) Innovative algorithms for prioritised AR/VR content delivery. In: 2018 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), 6-8 June 2018, Valencia, Spain.

Abstract
This paper proposes, describes and analyses two innovative approaches which make use of the Multipath Transmission Control Protocol (MPTCP) and its multiple flows for prioritised AR/VR content delivery. The first approach involves delivery of prioritised data using a fixed subflow and therefore establishment of a virtual private channel (VPC) for sending data. The second approach introduces a novel QoS on-the-fly (QoSF) algorithm that evaluates all subflows’ delivery performance and dynamically selects one of them to deliver the prioritised content with the lowest latency. Both algorithms are assessed in singlehomed and multi-homed configurations and present different performance improvements in comparison to the classic MPTCP. While QoSF algorithm demonstrates the best performance in scenarios where the delivery latency variation between subflows is high, the VPC algorithm has the best results in scenarios where this variation is smaller.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:MPTCP; QoS; AR/VR; prioritised content delivery
Subjects:Computer Science > Computer networks
Computer Science > Computer software
Computer Science > Machine learning
Computer Science > Multimedia systems
Engineering > Electronic engineering
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Institutes and Centres > Lero: The Irish Software Engineering Research Centre
Published in: 2018 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). . IEEE.
Publisher:IEEE
Official URL:https://dx.doi.org/10.1109/BMSB.2018.8436823
Copyright Information:© 2018 IEEE
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement no. 688503 for the NEWTON project (http://newtonproject.eu).
ID Code:26038
Deposited On:28 Jun 2021 10:42 by Fabio Rodrigues Da silva . Last Modified 28 Jun 2021 11:15
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