QoE-Driven, Energy-Aware Video Adaptation in 5G Networks: The SELFNET Self-Optimisation Use Case
Open accessAbstract
Sharp increase of video traffic is expected to account for the majority of traffic in future 5G networks. This paper introduces the SELFNET 5G project and describes the video streaming use case that will be used to demonstrate the self-optimising capabilities of SELFNET's autonomic network management framework. SELFNET's framework will provide an advanced self-organizing network (SON) underpinned by seamless integration of Software Defined Networking (SDN), Network Function Virtualization (NFV), and network intelligence. The self-optimisation video streaming use case is going beyond traditional quality of service approaches to network management. A set of monitoring and analysis components will facilitate a user-oriented, quality of experience (QoE) and energy-aware approach. Firstly, novel SON-Sensors will monitor both traditional network state metrics and new video and energy related metrics. The combination of these low level metrics provides highly innovative health of network (HoN) composite metrics. HoN composite metrics are processed via autonomous decisions not only maintaining but also proactively optimising users' video QoE while minimising the end-to-end energy consumption of the 5G network. This contribution provided a detailed technical overview of this ambitious use case.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Recent efforts exploring QoE management using SDN and/or NFV are limited by a limited review and discussion of standardization activities related to SDN and/or NFV.
“Although recent efforts explore the QoE management aspects using SDN and/or NFV, we note that these works are limited in at least one of the following: 1) limited review and discussion of the standardization activities related to SDN and/or NFV;”
From QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey (2020) · cites this paper as [24]
Cites
Overview of the High Efficiency Video Coding (HEVC) Standard
Sullivan, G. J., Ohm, J.-R., Han, W.-J., & Wiegand, T. (2012) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2012.2221191 · Cited by 8,286 · see citing works
Overview of the H.264/AVC video coding standard
Wiegand, T., Sullivan, G. J., Bjøntegaard, G., & Luthra, A. K. (2003) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2003.815165 · Cited by 8,192 · see citing works
Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C. K., & Zhang, J. C. (2014) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2014.2328098 · Cited by 8,106 · see citing works
Overview of the Scalable Video Coding Extension of the H.264/AVC Standard
Schwarz, H., Marpe, D., & Wiegand, T. (2007) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2007.905532 · Cited by 3,557 · see citing works
GreenCloud: a packet-level simulator of energy-aware cloud computing data centers
Kliazovich, D., Bouvry, P., & Khan, S. U. (2010) · The Journal of Supercomputing · doi:10.1007/s11227-010-0504-1 · Cited by 556 · see citing works
High Efficiency Video Coding: Coding Tools and Specification
Wien, M. (2014) · doi:10.1007/978-3-662-44276-0 · Cited by 352 · see citing works
Overview on Selective Encryption of Image and Video: Challenges and Perspectives
Massoudi, A., Lefebvre, F., De Vleeschouwer, C., Macq, B., & Quisquater, J.-J. (2008) · EURASIP Journal on Information Security · doi:10.1155/2008/179290 · Cited by 172 · see citing works
Optimized Rate-Distortion Extraction With Quality Layers in the Scalable Extension of H.264/AVC
Amonou, I., Cammas, N., Kervadec, S., et al. (2007) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2007.906870 · Cited by 119 · see citing works
On assuring end-to-end QoE in next generation networks: challenges and a possible solution
Zhang, J., & Ansari, N. (2011) · IEEE Communications Magazine · doi:10.1109/mcom.2011.5936172 · Cited by 108 · see citing works
Encryption for high efficiency video coding with video adaptation capabilities
Wallendael, G. V., Bohó, A., Cock, J. D., Munteanu, A., & Rik Van De Walle, B. (2013) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2013.6626250 · Cited by 80 · see citing works
Nakasu, E. (2012) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2011.2179821 · Cited by 69 · see citing works
Content-Based Video Quality Prediction for HEVC Encoded Videos Streamed Over Packet Networks
Anegekuh, L., Sun, L., Jammeh, E., et al. (2015) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2015.2444098 · Cited by 60 · see citing works
Optimized Rate-Distortion Extraction with Quality Layers
Amonou, I., Cammas, N., Kervadec, S., et al. (2006) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2006.312361 · Cited by 48 · see citing works
Design of a mobile video streaming system using adaptive spatial resolution control
Lee, H.-J., Lee, Y., Lee, J.-H., et al. (2009) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2009.5278043 · Cited by 34 · see citing works
Comparison of H.265 and VP9 coding efficiency for full HDTV and ultra HDTV applications
Kufa, J., & Kratochvíl, T. (2015) · International Conference Radioelektronika · doi:10.1109/radioelek.2015.7128999 · Cited by 20 · see citing works
QoE-Based SVC Layer Dropping in LTE Networks Using Content-Aware Layer Priorities
Fu, B., Staehle, D., Kunzmann, G., et al. (2015) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/2754167 · Cited by 14 · see citing works
Selective video encryption using chaotic system in the SHVC extension
Hamidouche, W., Farajallah, M., Raulet, M., et al. (2015) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2015.7178273 · Cited by 14 · see citing works
Video adaptation for consumer devices: opportunities and challenges offered by new standards
Nightingale, J., Wang, Q., Grecos, C., et al. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6979968 · Cited by 11 · see citing works
Self-citationDeriving video content type from HEVC bitstream semantics
Nightingale, J., Wang, Q., Grecos, C., & Goma, S. R. (2014) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2051757 · Cited by 8 · see citing works
Self-citationNightingale, J., Wang, Q., Grecos, C., et al. (2014) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2036721 · Cited by 6 · see citing works
Self-citationEstimation of Scalable Video adaptation parameters for Media Aware Network Elements
Ramakrishna, M. V., & Karunakar, A. K. (2014) · doi:10.1109/comsnets.2014.6734931 · Cited by 5 · see citing works
Review of Existing Objective QoE Methodologies
Fang, Y., Lin, W., & WINKLER, S. S. (2015) · Wiley eBooks · doi:10.1002/9781118736135.ch3 · Cited by 5 · see citing works
YouQoS - Combining Quality of Service with Network Neutrality
Liß̈, C., Fendler, T., Gajic, D., et al. (2015) · Cited by 1 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey
Barakabitze, A. A., Barman, N., Ahmad, A., Zadtootaghaj, S., Sun, L., Martini, M. G., & Atzori, L. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2958784 · Cited by 239 · see citing works
- Authors
- Nightingale, J., Wang, Q., Alcaraz Calero, J. M., Chirivella-Perez, E., Ulbricht, M., Alonso-López, J. A., Preto, R., Batista, T., Teixeira, T., Barros, M. J., & Reinsch, C.
- Affiliations
- University of the West of Scotland (GB)
- Artificial Intelligence, Visual Communications and Networks Research Centre, School of Engineering & Computing, University of the West of Scotland, Paisley PA1 2BE, UK
- InnoRoute GmbH, Marsstraße 14a, 80335 Munich, Germany
- Alvarion, 48091 Tel Aviv, Israel
- Ubiwhere (Portugal) (PT)
- Eurescom Gmbh, 69123 Heidelberg, Germany
- Corresponding author
- Nightingale, James
- ORCID
- Venue
- International Journal of Distributed Sensor Networks
- Publisher
- SAGE Publications
- Published
- 2016-01-01
- Volume
- 12
- Issue
- 1
- Pages
- 7829305
- ISSN
- 1550-1329 (ISSN-L)
- 1550-1477
- OpenAlex
- W2284873678
- Cited by
- 19
- References
- 23
- Citations by year
- 2024: 3 · 2023: 1 · 2022: 5 · 2020: 2 · 2019: 2 · 2017: 3 · 2016: 3
- FWCI
- 2.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- International Journal of Distributed Sensor Networks (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- European Commission Horizon 2020 5G-PPP Programme (H2020-ICT-2014-2/671672-SELFNET)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Optical Network Technologies
- Keywords
- 5G, video streaming, quality of experience, autonomic network management, software-defined networking, network function virtualization, network intelligence, network monitoring
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
