Recently published paper
A Reinforcement Learning-Based Routing for Real-Time Multimedia Traffic Transmission over Software-Defined Networking
1Department of Computing, University of Northampton, Northampton NN1 5PH, UK2Department of Computer Network, College of Information Technology, University of Babylon, Babil 51001, Iraq3School of Computing, Canterbury Christ Church University, Canterbury CT1 1QU, UK4Department of Technical and Applied Computing, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK*Electronics 2022, 11(15), 2441; https://doi.org/10.3390/electronics11152441 Published: 5 August 2022
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Recently, video streaming services consumption has grown massively and is foreseen to increase even more in the future. The tremendous traffic usage has negatively impacted the network’s quality of service due to network congestion and end-to-end customers’ satisfaction represented by the quality of experience, especially during evening peak hours. This paper introduces an intelligent multimedia framework that aims to optimise the network’s quality of service and users’ quality of experience by taking into account the integration of Software-Defined Networking and Reinforcement Learning, which enables exploring, learning, and exploiting potential paths for video streaming flows. Moreover, an objective study was conducted to assess video streaming for various realistic network environments and under low and high traffic loads to obtain two quality of experience metrics; video multimethod assessment fusion and structural similarity index measure. The experimental results validate the effectiveness of the proposed solution strategy, which demonstrated better viewing quality by achieving better customers’ quality of experience, higher throughput and lower data loss compared with the currently existing solutions.
Al Jameel, M.; Kanakis, T.; Turner, S.; Al-Sherbaz, A.; Bhaya, W.S. A Reinforcement Learning-Based Routing for Real-Time Multimedia Traffic Transmission over Software-Defined Networking. Electronics 2022, 11, 2441. https://doi.org/10.3390/electronics11152441
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Barakabitze, A.A. QoE-Centric Control and Management of Multimedia Services in Software Defined and Virtualized Networks. Ph.D. Thesis, University of Plymouth, Plymouth, UK, 2020.
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Huang, X.; Yuan, T.; Qiao, G.; Ren, Y. Deep reinforcement learning for multimedia traffic control in software defined networking. IEEE Netw. 2018, 32, 35-41.
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https://doi.org/10.1109/COMSNETS48256.2020.9027383
Anand, D.; Togou, M.A.; Muntean, G.M. A Machine Learning Solution for Automatic Network Selection to Enhance Quality of Service for Video Delivery. In Proceedings of the 2021 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Chengdu, China, 4-6 August 2021; pp. 1-5.
https://doi.org/10.1109/BMSB53066.2021.9547176
Kattadige, C.; Raman, A.; Thilakarathna, K.; Lutu, A.; Perino, D. 360NorVic: 360-degree video classification from mobile encrypted video traffic. In Proceedings of the 31st ACM Workshop on Network and Operating Systems Support for Digital Audio and Video, Istanbul, Turkey, 28 September-1 October 2021; pp. 58-65.
https://doi.org/10.1145/3458306.3460998
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Egilmez, H.E.; Civanlar, S.; Tekalp, A.M. An optimization framework for QoS-enabled adaptive video streaming over OpenFlow networks. IEEE Trans. Multimed. 2012, 15, 710-715.
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Juttner, A.; Szviatovski, B.; Mécs, I.; Rajkó, Z. Lagrange relaxation based method for the QoS routing problem. In Proceedings of the Conference on Computer Communications-Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No. 01CH37213), Anchorage, AK, USA, 22-26 April 2001; Volume 2, pp. 859-868.
Yu, T.F.; Wang, K.; Hsu, Y.H. Adaptive routing for video streaming with QoS support over SDN networks. In Proceedings of the 2015 International Conference on Information Networking (ICOIN), Siem Reap, Cambodia, 12-14 January 2015; pp. 318-323.
Ongaro, F.; Cerqueira, E.; Foschini, L.; Corradi, A.; Gerla, M. Enhancing the quality level support for real-time multimedia applications in software-defined networks. In Proceedings of the 2015 International Conference on Computing, Networking and Communications (ICNC), Garden Grove, CA, USA, 16-19 February 2015; pp. 505-509.
https://doi.org/10.1109/ICCNC.2015.7069395
Rego, A.; Sendra, S.; Jimenez, J.M.; Lloret, J. OSPF routing protocol performance in Software Defined Networks. In Proceedings of the 2017 Fourth International Conference on Software Defined Systems (SDS), Valencia, Spain, 8-11 May 2017; pp. 131-136. [Google Scholar]
https://doi.org/10.1109/SDS.2017.7939153
Rego, A.; Sendra, S.; Jimenez, J.M.; Lloret, J. Dynamic metric OSPF-based routing protocol for software defined networks. Clust. Comput. 2019, 22, 705-720.
https://doi.org/10.1007/s10586-018-2875-7
Elbasheer, M.O.; Aldegheishem, A.; Lloret, J.; Alrajeh, N. A QoS-Based routing algorithm over software defined networks. J. Netw. Comput. Appl. 2021, 194, 103215.
https://doi.org/10.1016/j.jnca.2021.103215
Uzakgider, T.; Cetinkaya, C.; Sayit, M. Learning-based approach for layered adaptive video streaming over SDN. Comput. Netw. 2015, 92, 357-368. [Google Scholar] [CrossRef]
https://doi.org/10.1016/j.comnet.2015.09.027
Sendra, S.; Rego, A.; Lloret, J.; Jimenez, J.M.; Romero, O. Including artificial intelligence in a routing protocol using software defined networks. In Proceedings of the 2017 IEEE International Conference on Communications Workshops (ICC Workshops), Paris, France, 21-23 May 2017; pp. 670-674.
https://doi.org/10.1109/ICCW.2017.7962735
Al-Jawad, A.; Shah, P.; Gemikonakli, O.; Trestian, R. LearnQoS: A learning approach for optimizing QoS over multimedia-based SDNs. In Proceedings of the 2018 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Valencia, Spain, 6-8 June 2018; pp. 1-6.
https://doi.org/10.1109/BMSB.2018.8436781
Hossain, M.B.; Wei, J. Reinforcement learning-driven QoS-aware intelligent routing for software-defined networks. In Proceedings of the 2019 IEEE global conference on signal and information processing (GlobalSIP), Ottawa, ON, Canada, 11-14 November 2019; pp. 1-5.
https://doi.org/10.1109/GlobalSIP45357.2019.8969320
Godfrey, D.; Kim, B.S.; Miao, H.; Shah, B.; Hayat, B.; Khan, I.; Sung, T.E.; Kim, K.I. Q-learning based routing protocol for congestion avoidance. Comput. Mater. Contin. 2021, 68, 3671.
https://doi.org/10.32604/cmc.2021.017475
Al-Jawad, A.; Comşa, I.S.; Shah, P.; Gemikonakli, O.; Trestian, R. An innovative reinforcement learning-based framework for quality of service provisioning over multimedia-based sdn environments. IEEE Trans. Broadcast. 2021, 67, 851-867.
https://doi.org/10.1109/TBC.2021.3099728
Al-Jawad, A.; Comşa, I.-S.; Shah, P.; Gemikonakli, O.; Trestian, R. REDO: A reinforcement learning-based dynamic routing algorithm selection method for SDN. In Proceedings of the 2021 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), Online, 9-11 November 2021; pp. 54-59.
https://doi.org/10.1109/NFV-SDN53031.2021.9665140
Guo, Y.; Wang, W.; Zhang, H.; Guo, W.; Wang, Z.; Tian, Y.; Yin, X.; Wu, J. Traffic Engineering in hybrid Software Defined Network via Reinforcement Learning. J. Netw. Comput. Appl. 2021, 189, 103116.
https://doi.org/10.1016/j.jnca.2021.103116
Liu, W.x.; Cai, J.; Chen, Q.C.; Wang, Y. DRL-R: Deep reinforcement learning approach for intelligent routing in software-defined data-center networks. J. Netw. Comput. Appl. 2021, 177, 102865.
https://doi.org/10.1016/j.jnca.2020.102865
Gueant, V. iPerf-The Ultimate Speed Test Tool for TCP, UDP and SCTPTEST the Limits of Your Network + Internet Neutrality Test. Available online: https://iperf.fr/ (accessed on 10 December 2021).
Asadollahi, S.; Goswami, B.; Sameer, M. Ryu controller's scalability experiment on software defined networks. In Proceedings of the 2018 IEEE international conference on current trends in advanced computing (ICCTAC), Bangalore, India, 1-2 February 2018; pp. 1-5.
https://doi.org/10.1109/ICCTAC.2018.8370397
Vega, M.T.; Perra, C.; Liotta, A. Resilience of video streaming services to network impairments. IEEE Trans. Broadcast. 2018, 64, 220-234. [Google Scholar] [CrossRef]
https://doi.org/10.1109/TBC.2017.2781125
Kim, H.J.; Yun, D.G.; Kim, H.S.; Cho, K.S.; Choi, S.G. QoE assessment model for video streaming service using QoS parameters in wired-wireless network. In Proceedings of the 2012 14th International Conference on Advanced Communication Technology (ICACT), Pyeongchang, Korea, 19-22 February 2012; pp. 459-464.
Chen, Y.; Wu, K.; Zhang, Q. From QoS to QoE: A tutorial on video quality assessment. IEEE Commun. Surv. Tutor. 2014, 17, 1126-1165.
https://doi.org/10.1109/COMST.2014.2363139
Oginni, O.; Bull, P.; Wang, Y. Constraint-aware software-defined network for routing real-time multimedia. ACM SIGBED Rev. 2018, 15, 37-42.
https://doi.org/10.1145/3267419.3267425
Benmir, A.; Korichi, A.; Bourouis, A.; Alreshoodi, M.; Al-Jobouri, L. GeoQoE-Vanet: QoE-aware geographic routing protocol for video streaming over vehicular ad-hoc networks. Computers 2020, 9, 45.
https://doi.org/10.3390/computers9020045
Mammeri, Z. Reinforcement learning based routing in networks: Review and classification of approaches. IEEE Access 2019, 7, 55916-55950.
https://doi.org/10.1109/ACCESS.2019.2913776
Sutton, R.S.; Barto, A.G. Reinforcement Learning: An Introduction; MIT Press: Cambridge, MA, USA, 2018. [
Juluri, P.; Tamarapalli, V.; Medhi, D. Measurement of quality of experience of video-on-demand services: A survey. IEEE Commun. Surv. Tutor. 2015, 18, 401-418.
https://doi.org/10.1109/COMST.2015.2401424
Al Shalabi, L.; Shaaban, Z. Normalization as a preprocessing engine for data mining and the approach of preference matrix. In Proceedings of the 2006 International Conference on Dependability of Computer Systems, Szklarska Poręba, Poland, 25-27 May 2006; pp. 207-214.
https://doi.org/10.1109/DEPCOS-RELCOMEX.2006.38
de Oliveira, R.L.S.; Schweitzer, C.M.; Shinoda, A.A.; Prete, L.R. Using Mininet for emulation and prototyping Software-Defined Networks. In Proceedings of the 2014 IEEE Colombian Conference on Communications and Computing (COLCOM), Bogota, Colombia, 4-6 June 2014; pp. 1-6.
https://doi.org/10.1109/ColComCon.2014.6860404
Henni, D.E.; Ghomari, A.; Hadjadj-Aoul, Y. A consistent QoS routing strategy for video streaming services in SDN networks. Int. J. Commun. Syst. 2020, 33, e4177.
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