On the Load Balancing of Edge Computing resources for on-line video delivery

Journal article


Bulkan, U, Dagiuklas, T, Iqbal, M, Saidul Huq, M, Al-Dulaimi, A and Rodriguez, J (2018). On the Load Balancing of Edge Computing resources for on-line video delivery. IEEE Access. 6 (2018), pp. 73916-73927.
AuthorsBulkan, U, Dagiuklas, T, Iqbal, M, Saidul Huq, M, Al-Dulaimi, A and Rodriguez, J
Abstract

Online video broadcasting platforms are distributed, complex, cloud oriented, scalable, micro-service based systems that are intended to provide Over-The-Top (OTT) and live content to audience in scattered geographic locations. Due to the nature of cloud VM hosting costs, the subscribers are usually served under limited resources in order to minimize delivery budget. However, operations including transcoding require high computational capacity and any disturbance in supplying requested demand might result in Quality of Experience (QoE)
deterioration. For any online delivery deployment, understanding
users QoE plays a crucial role for rebalancing cloud resources.
In this work, a methodology for estimating Quality of Experience
is provided for a scalable cloud based online video platform. The
model will provide an adeptness guideline regarding limited cloud
resources and relate computational capacity, memory, transcoding
and throughput capability and finally latency competence of
the cloud service to QoE. Scalability and efficiency of the system
are optimized through reckoning sufficient number of VMs and
containers to satisfy the user requests even on peak demand
durations with minimum number of VMs. Both horizontal and
vertical scaling strategies (including VM migration) are modelled
to cover up availability and reliability of intermediate and edge
Content Delivery Network (CDN) cache nodes

Year2018
JournalIEEE Access
Journal citation6 (2018), pp. 73916-73927
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN2169-3536
Digital Object Identifier (DOI)doi:10.1109/ACCESS.2018.2883319
Publication dates
Print30 Nov 2018
Publication process dates
Deposited04 Dec 2018
Accepted08 Nov 2018
Accepted author manuscript
License
CC BY 4.0
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https://openresearch.lsbu.ac.uk/item/8687q

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