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Crowdsourcing Framework for QoE-Aware SD-WAN
Shahram Shah Heydari
University of Ontario Institute of Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0002-6107-7728
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The exponential increase in bandwidth-sensitive multimedia traffic on the Internet has created new challenges and opportunities. With the shifting focus from service availability to service quality, there is a need to have quality management measures to serve the high needs of efficient transmission and delivery in time-constrained environments over IP networks. Quality of Experience (QoE) is now considered the most important measure to achieve the twin goals of application efficiency and user satisfaction from a user perspective. In this paper, we propose a framework that can be used to collect real-time QoE feedback through crowdsourcing and forward it to SD-WAN controllers to enhance streaming routes based on real-time user quality perceptions. We analyze how QoE can be affected by different network conditions, and how different streaming protocols compare against each other when the network parameters change dynamically. We compare the real-time user feedback to predefined network changes to measure if participants will be able to identify all degradation events, and to examine which combination of degradation events are noticeable to the participants. These QoE timestamped feedback is sent back to the SD-WAN controller continuously in order to locate problems and bottlenecks in the current service paths and to enable network controllers to take corrective action by rerouting the streamed traffic. Our aim is to demonstrate that real-time QoE feedback can enhance cloud-based services and can adjust services quality based on real-time, active participants’ interaction[1].
[1] This paper extends the preliminary results presented by the authors at the PVE-SDN 2019 workshop in IEEE Conference on Network Softwarization (NetSoft 2019).
Keywords
QoE, SDN, QoS, crowdsourcing
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Editorial decision: Major revision
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Review #2 received
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Received 03 Sep, 2020
Reviewer #1 agreed
On 12 Aug, 2020
Reviewer #2 agreed
On 12 Aug, 2020
Reviewers invited
Invitations sent on 11 Aug, 2020
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On 24 May, 2020
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On 23 May, 2020
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On 23 May, 2020
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This preprint is under consideration at Journal of Internet Services and Applications. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Crowdsourcing Framework for QoE-Aware SD-WAN
Shahram Shah Heydari
University of Ontario Institute of Technology
Corresponding Author
ORCiD: https://orcid.org/0000-0002-6107-7728
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 2
Posted 13 Jan, 2021
No community comments so far
Reviewer #1 agreed
On 03 Jan, 2021
Reviewers invited
Invitations sent on 28 Dec, 2020
Editor assigned
On 27 Dec, 2020
Submission checks complete
On 27 Dec, 2020
Editor invited
On 27 Dec, 2020
No comments provided
Editorial decision: Major revision
On 26 Oct, 2020
Review #2 received
Received 03 Sep, 2020
Review #1 received
Received 03 Sep, 2020
Reviewer #1 agreed
On 12 Aug, 2020
Reviewer #2 agreed
On 12 Aug, 2020
Reviewers invited
Invitations sent on 11 Aug, 2020
Editor assigned
On 24 May, 2020
Submission checks complete
On 23 May, 2020
Editor invited
On 23 May, 2020
First submitted
On 22 May, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The exponential increase in bandwidth-sensitive multimedia traffic on the Internet has created new challenges and opportunities. With the shifting focus from service availability to service quality, there is a need to have quality management measures to serve the high needs of efficient transmission and delivery in time-constrained environments over IP networks. Quality of Experience (QoE) is now considered the most important measure to achieve the twin goals of application efficiency and user satisfaction from a user perspective. In this paper, we propose a framework that can be used to collect real-time QoE feedback through crowdsourcing and forward it to SD-WAN controllers to enhance streaming routes based on real-time user quality perceptions. We analyze how QoE can be affected by different network conditions, and how different streaming protocols compare against each other when the network parameters change dynamically. We compare the real-time user feedback to predefined network changes to measure if participants will be able to identify all degradation events, and to examine which combination of degradation events are noticeable to the participants. These QoE timestamped feedback is sent back to the SD-WAN controller continuously in order to locate problems and bottlenecks in the current service paths and to enable network controllers to take corrective action by rerouting the streamed traffic. Our aim is to demonstrate that real-time QoE feedback can enhance cloud-based services and can adjust services quality based on real-time, active participants’ interaction[1].
[1] This paper extends the preliminary results presented by the authors at the PVE-SDN 2019 workshop in IEEE Conference on Network Softwarization (NetSoft 2019).
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