Conference paper Open Access

Self-Restoring Video User Experience in 5G Networks Based on a Cognitive Network Management Framework

Pablo Salva-Garcia; Jose M. Alcaraz-Calero; Qi Wang; Maria Barros; Anastasius Gavras

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  <identifier identifierType="DOI">10.5281/zenodo.3741342</identifier>
      <creatorName>Pablo Salva-Garcia</creatorName>
      <affiliation>University of the West of Scotland</affiliation>
      <creatorName>Jose M. Alcaraz-Calero</creatorName>
      <affiliation>University of the West of Scotland</affiliation>
      <creatorName>Qi Wang</creatorName>
      <affiliation>University of the West of Scotland</affiliation>
      <creatorName>Maria Barros</creatorName>
      <affiliation>Eurescom GmbH</affiliation>
      <creatorName>Anastasius Gavras</creatorName>
      <affiliation>Eurescom GmbH</affiliation>
    <title>Self-Restoring Video User Experience in 5G Networks Based on a Cognitive Network Management Framework</title>
    <subject>5G; Artificial Intelligence; Video.</subject>
    <date dateType="Issued">2020-04-06</date>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3741341</relatedIdentifier>
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    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;Video applications such as streaming are expected to dominate the traffic of the incoming Fifth generation (5G) networks. It is essential for 5G service video providers and/or network operators to provide assurances for both the overall status of the network and the quality of their video transmissions in order to meet the final users&amp;rsquo; expectations. In this contribution, we propose a video optimisation scheme which is implemented as a Virtualised Network Function (VNF), which in turn, facilitates its on-demand deployment in a flexible way&lt;br&gt;
in response to an intelligent analysis of the current network traffic conditions. We leverage a cognitive network management framework to analyse both network status metrics and video stream requirements to evaluate if any optimisation action is required. The testing and evaluation focus on the functional tests and scalability evaluation of the proposed scheme. Moreover, the bandwidth saving is assessed to demonstrate the significant benefit in traffic reduction for a 5G system that adopts the proposed approach.&lt;/p&gt;</description>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/761913/">761913</awardNumber>
      <awardTitle>End-to-End Cognitive Network Slicing and Slice Management Framework in Virtualised Multi-Domain, Multi-Tenant 5G Networks</awardTitle>
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