Virtualized Module for Distributed Quality Assessment Applied to Video Streaming in 5G Networks Environments

EasyChair Preprint no. 310

Abstract

The success of streaming platforms and the expansion of advanced multimedia formats, such as UHD that presents 4K and 8K resolutions, demand better network conditions for transmitting higher amounts of data. 5G Networks offer a collection of improvements over their predecessors including an increase of bandwidth and lower latency. Additionally, 5G architecture allows the network nodes to improve their capabilities with the inclusion of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) technologies, which provide an opportunity to control media flows and distribute the processing tools through the delocation of remote virtual machines. As a consequence of this fact, different types of applications for broadcast and multimedia analysis can be implemented for different purposes in the network distribution chain, such as image or audio assessment, video edition, metadata addition and other kinds of system processing. For this paper, among these applications, we present a software module that is able to assess video quality when applied in any point of the network in order to determine remotely the state of the network. This module known as "probe" checks the transmission through image evaluation metrics and sends a resulting report to the network backbone for communication the retransmission if necessary, to fulfill the requirements and demands of the users. Tests developed in different network distributions and with a variety of video sequences demonstrate the validity of this innovative software.

Keyphrases: 5G networks, artefacts, Multimedia, NFV, QoE, SDN, Streaming., video quality assessment, Virtualization

@Booklet{EasyChair:310,
  author = {Juan Pedro López and David Jiménez and Juan Antonio Rodrigo and Nuria Sánchez and José Manuel Menéndez and Federico Álvarez and José María Lalueza},
  title = {Virtualized Module for Distributed Quality Assessment Applied to Video Streaming in 5G Networks Environments},
  howpublished = {EasyChair Preprint no. 310},
  doi = {10.29007/pntm},
  year = {EasyChair, 2018}}