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Future Intent-Based Networking for QoE-Driven Business Models

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Future Intent-Based Networking

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 831))

Abstract

The Quality of Experience (QoE) business aspect will be one of the media value chains of the future networking. Therefore, new Service Level Agreements (SLAs) such as Experience Level Agreements (ELAs), which are based solely on QoE, should be the main pinnacle of future intent-based networking (IBN) projects to improve business and customers quality. Moreover, we present intent-based network management using Software-Defined Network (SDN) perspective in relation to QoE-business aspects. In this chapter we proposed a conceptual model for the construction of a heterogeneous software-defined intent-based network. This model allows providing effective distribution and redistribution of common resources adapting to the changing requirements of business customers regarding the Quality of Service (QoS) provision. It is proposed to use a comprehensive indicator of QoS for users, formed in the form of QoE assessment. This is the main criterion for adaptive management of resource reallocation in the context of changes in the importance of business processes in the IBN concept implementation. The proposed model of IBN allows to guarantee the ordered level of service by analyzing QoE estimates of users according to the new ELA contract. The model also makes use machine-learning capabilities to manage the network in response to changing business requirements. They are used to regulate and perform routine tasks, adjust policies, respond to system events, and verify that necessary goals are met and actions are taken. The system not only configures changes to the network, but also enforces them and makes the necessary adjustments. In addition, such a system is considered the next stage in the development of SDN and is based on the principles of intelligence and software infrastructure to provide a higher level of analysis and determine which tasks need to be automatized.

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References

  1. Kir, H., Erdogan, N.: A knowledge-intensive adaptive business process management framework. Inf. Syst. 95, 101639 (2021)

    Article  Google Scholar 

  2. Torkhani, R., Laval, J., Malek, H., Moalla, N.: Intelligent framework for business process automation and re-engineering. Int. Conf. Intell. Syst. 2018, 624–629 (2018). https://doi.org/10.1109/IS.2018.8710523

    Article  Google Scholar 

  3. Klymash, M., Beshley, M., Koval, V.: The model of prioritization of services for efficient usage of multiservice network resources. In: Proceedings of International Conference on Modern Problem of Radio Engineering, Telecommunications and Computer Science, pp. 320–321 (2012)

    Google Scholar 

  4. EL-ezzi, Z.Q., Al-Dulaimi, A.M., Ibrahim, A.A.: Personalized quality of experience (QOE) management using data driven architecture in 5G wireless networks. In: 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), pp. 1–10 (2020). https://doi.org/10.1109/ISMSIT50672.2020.9254863

  5. Marchão, J., Reis, L., Martins, P.V.: Business areas and processes alignment in ICT framework. In: 2020 15th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–4 (2020). https://doi.org/10.23919/CISTI49556.2020.9141067

  6. Romanchuk, V., Beshley, M., Polishuk, A., Seliuchenko, M.: Method for processing multiservice traffic in network node based on adaptive management of buffer resource. In: 2018 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET), pp. 1118–1122 (2018). https://doi.org/10.1109/TCSET.2018.8336390

  7. Beshley, M., Kryvinska, N., Seliuchenko, M., Beshley, H., Shakshuki, E., Yasar, A.: End-to-end QoS “smart queue” management algorithms and traffic prioritization mechanisms for narrow-band internet of things services in 4G/5G networks. Sensors 20(8), 2324-1–2324-30 (2020)

    Google Scholar 

  8. Kryvinska, N.: An analytical approach for the modeling of real-time services over IP network. In: Elsevier Transactions of IMACS, Journal Mathematics and Computers in Simulation (MATCOM), vol. 79, pp. 980–990 (2008). ISSN: 0378-4754. https://doi.org/10.1016/j.matcom.2008.02.016

  9. Seliuchenko, M., Beshley, M., Kyryk, M., Zhovtonoh, M.: Automated recovery of server applications for SDN-based internet of things. In: 2019 3rd International Conference on Advanced Information and Communications Technologies (AICT), pp. 149–152 (2019). https://doi.org/10.1109/AIACT.2019.8847743

  10. Jun, S., et al.: A cost-efficient software based router and traffic generator for simulation and testing of IP network. Electronics 9(1), 40-1–40-24 (2020)

    Google Scholar 

  11. Kryvinska, N.: Intelligent network analysis by closed queuing models. Telecommun. Syst. 27, 85–98 (2004). https://doi.org/10.1023/B:TELS.0000032945.92937.8f

    Article  Google Scholar 

  12. Panchenko, O., et al.: Method for adaptive client-oriented management of quality of service in integrated SDN/CLOUD networks. In: 2017 4th International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T), Kharkov, pp. 452–455 (2017)

    Google Scholar 

  13. Mandal, S.K., Ogras, U.Y., Rao Doppa, J., Ayoub, R.Z., Kishinevsky, M., Pande, P.P.: Online adaptive learning for runtime resource management of heterogeneous SoCs. In: 2020 57th ACM/IEEE Design Automation Conference (DAC), pp. 1–6 (2020). https://doi.org/10.1109/DAC18072.2020.9218604

  14. Schulz, D.: Intent-based automation networks: toward a common reference model for the self-orchestration of industrial intranets. In: IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society, pp. 4657–4664 (2016). https://doi.org/10.1109/IECON.2016.7792959

  15. Farahnakian, F., Bahsoon, R., Liljeberg, P., Pahikkala, T.: Self-adaptive resource management system in IaaS clouds. In: 2016 IEEE 9th International Conference on Cloud Computing (CLOUD), pp. 553–560 (2016). https://doi.org/10.1109/CLOUD.2016.0079

  16. Rafiq, A., Mehmood, A., Song, W.-C.: Intent-Based slicing between containers in SDN overlay network. J. Commun. 15(3), 237–244 (2020). https://doi.org/10.12720/jcm.15.3.237-244

    Article  Google Scholar 

  17. Singh, A., Aujla, G.S., Bali, R.S.: Intent-based network for data dissemination in software-defined vehicular edge computing. IEEE Trans. Intell. Transport. Syst. 22(8), 5310−5318. https://doi.org/10.1109/TITS.2020.3002349

  18. Rafiq, A., Afaq, M., Song, W.-C.: Intent-based networking with proactive load distribution in data center using IBN manager and smart path manager. J. Ambient. Intell. Humaniz. Comput. 11(11), 4855–4872 (2020). https://doi.org/10.1007/s12652-020-01753-1

    Article  Google Scholar 

  19. Hyun, J., Hong, J.W.: Knowledge-defined networking using in-band network telemetry. In: 2017 19th Asia-Pacific Network Operations and Management Symposium (APNOMS), pp. 54–57 (2017). https://doi.org/10.1109/APNOMS.2017.8094178

  20. Wu, C., Horiuchi, S., Tayama, K.: A resource design framework to realize intent-based cloud management. IEEE Int. Conf. Cloud Comput. Technol. Sci. 2019, 37–44 (2019). https://doi.org/10.1109/CloudCom.2019.00018

    Article  Google Scholar 

  21. Ujcich, B.E., Sanders, W.H.: Data protection intents for software-defined networking. IEEE Conf. Netw. Softwarization 2019, 271–275 (2019). https://doi.org/10.1109/NETSOFT.2019.8806684

    Article  Google Scholar 

  22. Beshley, M., Vesely, P., Prislupskiy, A., Beshley, H., Kyryk, M., Romanchuk, V., Kahalo, I.: Customer-oriented quality of service management method for the future intent-based networking. Appl. Sci. 10(22), 8223-1–8223-38 (2020)

    Google Scholar 

  23. Wang, L., Delaney, D.T.: QoE oriented cognitive network based on machine learning and SDN. In: 2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN), Chongqing, China, pp. 678–681 (2019)

    Google Scholar 

  24. Beshley, M., Pryslupskyi, A., Panchenko, O., Seliuchenko, M.: Dynamic switch migration method based on QoE- aware priority marking for intent-based networking. In: 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine, pp. 864–868 (2020)

    Google Scholar 

  25. Barakabitze, A.A., et al.: QoE management of multimedia streaming services in future networks: a tutorial and survey. IEEE Commun. Surv. Tutorials 22(1), 526–565 (2020)

    Google Scholar 

  26. Lewis, B., Fawcett, L., Broadbent, M., Race, N.: Using P4 to enable scalable intents in software defined networks. In: 2018 IEEE 26th International Conference on Network Protocols (ICNP), Cambridge, pp. 442–443 (2018)

    Google Scholar 

  27. Beshley, M., Pryslupskyi, A., Panchenko, O., Beshley, H.: SDN/cloud solutions for intent-based networking. In: 2019 3rd International Conference on Advanced Information and Communications Technologies (AICT), Lviv, Ukraine, pp. 22–25 (2019)

    Google Scholar 

  28. Abbas, K., Khan, T.A., Afaq, M., Song, W.-C.: Network slice lifecycle management for 5G mobile networks: an intent-based networking approach. IEEE Access 9, 80128–80146 (2021). https://doi.org/10.1109/ACCESS.2021.3084834

    Article  Google Scholar 

  29. Medvetskyi, M., Beshley, M., Klymash, M.: A quality of experience management method for intent-based software-defined networks. In: 2021 IEEE 16th International Conference on the Experience of Designing and Application of CAD Systems (CADSM), pp. 59–62 (2021). https://doi.org/10.1109/CADSM52681.2021.9385250

  30. Beshley, M., Kryvinska, N., Beshley, H., Yaremko, O., Pyrih, J.: Virtual router design and modeling for future networks with QoS guarantees. Electronics 10(10), 1139 (2021)

    Article  Google Scholar 

  31. Flores Moyano, R., Fernández, D., Merayo, N., Lentisco, C.M., Cárdenas, A.: NFV and SDN-based differentiated traffic treatment for residential networks. IEEE Access 8, 34038–34055 (2020). https://doi.org/10.1109/ACCESS.2020.2974504

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Acknowledgement

This research was supported by the Ukrainian government project №0120U102201 “Development of the methods and unified software-hardware means for the deployment of the energy efficient intent-based multi-purpose information and communication networks.”

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Authors and Affiliations

  1. Lviv Polytechnic National University, Lviv, 79013, Ukraine

    Mykola Beshley, Mykhailo Klymash, Halyna Beshley, Oksana Urikova & Yuriy Bobalo

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  1. Mykola Beshley
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  2. Mykhailo Klymash
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  3. Halyna Beshley
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  4. Oksana Urikova
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  5. Yuriy Bobalo
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Correspondence to Mykola Beshley .

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Editors and Affiliations

  1. Lviv Polytechnic National University, Lviv, Ukraine

    Mikhailo Klymash

  2. Lviv Polytechnic National University, Lviv, Ukraine

    Mykola Beshley

  3. Saxon Study Academy, BA Dresden University of Cooperative Education, Dresden, Germany

    Andriy Luntovskyy

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Beshley, M., Klymash, M., Beshley, H., Urikova, O., Bobalo, Y. (2022). Future Intent-Based Networking for QoE-Driven Business Models. In: Klymash, M., Beshley, M., Luntovskyy, A. (eds) Future Intent-Based Networking. Lecture Notes in Electrical Engineering, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-030-92435-5_1

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  • DOI: https://doi.org/10.1007/978-3-030-92435-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92433-1

  • Online ISBN: 978-3-030-92435-5

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