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Analysis of Mobile Communication Network Architecture Based on SDN

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Abstract

With the development of mobile network and the continuous improvement of network speed, the pressure of network traffic is becoming more and more prominent. In this context, the design of the fifth generation (5G) communication networks has become one of the key issues considered by operators. This paper studies a new open wireless access network architecture based on Software Defined Network (SDN) and Reservoir Computing (RC). On this basis, a scheme of air interface control and data separation in mobile communication network is designed. Firstly, through the advantage of the SDN, storage analysis of the energy cost of the underlying network equipment, the cost of virtual network resources and the average load of CPU are unified managed. Secondly, an adequate adaptive reservoir pool Echo State Network (ARP-ESN) model is proposed to enhance users’ traffic predicting. With the combination of global view resource state and precisely traffic predicting, the dynamic configuration of network resources under the specific business function chain is realized, so as to improve the utilization of the whole basic network resources. The simulation verifies the reliability and effectiveness of the algorithm. It can realize the rapid deployment of 5G mobile communication network and the flexible management and control of virtual network functional units, so as to improve the overall utilization of network resources.

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Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Kumar, D., Baranwal, G., Vidyarthi, D.P.: A survey on auction based approaches for resource allocation and pricing in emerging edge technologies. J Grid Comput. 20, 3 (2022)

    Article  Google Scholar 

  2. Low, W.S., Chan, C.K., Chuah, J.H., et al.: A review of machine learning network in human motion biomechanics. J Grid Comput. 20, 4 (2022)

    Article  Google Scholar 

  3. Ruggeri, A., Celesti, A., Fazio, M., et al.: An innovative Blockchain-based orchestrator for osmotic computing. J Grid Comput. 20, 2 (2022)

    Article  Google Scholar 

  4. Wang, S.H., Satapathy, S.C., Zhou, Q., et al.: Secondary pulmonary tuberculosis identification via pseudo-Zernike moment and deep stacked sparse autoencoder. J Grid Comput. 20, 1 (2022)

    Article  Google Scholar 

  5. Banerjee, S., Roy, S., Khatua, S.: SLA-aware stochastic load balancing in dynamic cloud environment. J Grid Comput. 19, 49 (2021)

    Article  Google Scholar 

  6. Maciel, D.B., Neto, E.P., Costa, K.B., et al.: Cloud-network slicing MANO towards an efficient IoT-cloud continuum. J Grid Comput. 19, 48 (2021)

    Article  Google Scholar 

  7. Nguyen, V.G., Brunstrom, A., Grinnemo, K.J., et al.: SDN/NFV-based Mobile packet Core network architectures: a survey. Comm Surv Tutorials, IEEE. 19(3), 1567–1602 (2017)

    Article  Google Scholar 

  8. Wang, K., Wang, Y., Zeng, D., et al.: An SDN-based architecture for next-generation wireless networks. IEEE Wirel. Commun. 24(1), 25–31 (2017)

    Article  MathSciNet  Google Scholar 

  9. Yang, F., Wang, H., Mei, C., et al.: A flexible three clouds 5G mobile network architecture based on NFV & SDN. Comm, China. 12(Supplement), 121–131 (2015)

    Article  Google Scholar 

  10. Ullah, A., Dagdeviren, H., Ariyattu, R.C., DesLauriers, J., Kiss, T., Bowden, J.: MiCADO-edge: towards an application-level orchestrator for the cloud-to-edge computing continuum. J Grid Comput. 19(4), 1–28 (2021)

    Article  Google Scholar 

  11. Moreno-Vozmediano, R., et al.: Orchestrating the deployment of high availability services on multi-zone and multi-cloud scenarios. J Grid Comput. 16(1), 39–53 (2018)

    Article  Google Scholar 

  12. Sankaravadivel, V., Thalavaipillai, S.: Symptoms based endometriosis prediction using machine learning. Bullet Electrical Eng Inform. 10(6), 3102–3109 (2021)

    Article  Google Scholar 

  13. Tong, H., et al.: Mobility-aware seamless handover with MPTCP in software-defined HetNets. IEEE Trans. Netw. Serv. Manag. 18(1), 498–510 (2021)

    Article  Google Scholar 

  14. Brogi, A., Forti, S., Guerrero, C., et al.: Declarative application Management in the fog. J Grid Computing. 19, 45 (2021)

    Article  Google Scholar 

  15. Nguyen, V.G., Do, T.X., Kim, Y.H.: SDN and virtualization-based LTE Mobile network architectures: a comprehensive survey. Wirel. Pers. Commun. 86(3), 1401–1438 (2016)

    Article  Google Scholar 

  16. Boero, L., Marchese, M., Patrone, F.: The impact of delay in software-defined integrated terrestrial-satellite networks. China Commun. 15(08), 21–31 (2018)

    Article  Google Scholar 

  17. Yang, P., Zhang, N., Bi, Y., et al.: Catalyzing cloud-fog interoperation in 5G wireless networks: an SDN approach. IEEE Netw. 31(5), 14–20 (2017)

    Article  Google Scholar 

  18. Gatellier, M.A., De Jonckheere, J., Storme, L., et al.: Fetal heart rate variability analysis for neonatal acidosis prediction. J. Clin. Monit. Comput. 35(4), 771–777 (2021)

    Article  Google Scholar 

  19. Ordonez-Lucena, J., Ameigeiras, P., Lopez, D., et al.: Network slicing for 5G with SDN/NFV: concepts, architectures and challenges. IEEE Commun. Mag. 55(5), 80–87 (2017)

    Article  Google Scholar 

  20. Costa-Perez, X., Garcia-Saavedra, A., Li, X., et al.: 5G-Crosshaul: an SDN/NFV integrated Fronthaul/backhaul transport network architecture. IEEE Wirel. Commun. 24(1), 38–45 (2017)

    Article  Google Scholar 

  21. Singh, M.: An overview of grid computing, 2019 international conference on computing, communication, and intelligent systems (ICCCIS). IEEE. 194–198 (2019)

  22. Chai, Y., Zeng, X.: Regional condition-aware hybrid routing protocol for hybrid wireless mesh network. Comput. Netw. 148, 120–128 (2019)

    Article  Google Scholar 

  23. Panda, S.: Energy efficient routing and lightpath management in software defined networking based inter-DC elastic optical networks. Opt. Fiber Technol. 55, 102–128 (2020)

    Article  Google Scholar 

  24. Chen, M., Saad, W., Yin, C., et al.: Echo state networks for proactive caching in cloud-based radio access networks with Mobile users[J]. IEEE Trans. Wirel. Commun. PP(99):1-1, (2017)

  25. Gallicchio, C., Micheli, A.: Tree Echo state networks. Neurocomputing. 101, 319–337 (2013)

    Article  Google Scholar 

  26. Meng, L., Zhang, J., Wang, Y.: Research on a new hybrid optimization algorithm based on QPSO and FNN. Int J Smart Home. 10(6), 175–186 (2016)

    Article  Google Scholar 

  27. Sepúlveda-Rodríguez, L.E., Garrido, J.L., Chavarro-Porras, J.C., et al.: Study-based systematic mapping analysis of cloud Technologies for Leveraging IT resource and service management: the case study of the science gateway approach. J Grid Comput. 19, 4 (2021)

    Article  Google Scholar 

  28. Ibrahim, A., Hashim, F., Noordin, N.K., et al.: Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture. IEEE Access. 9, 2602–2617 (2020)

    Article  Google Scholar 

  29. Ordonez-Lucena, J., Ameigeiras, P., Lopez, D., et al.: Network slicing for 5G with SDN/NFV: concepts, architectures and challenges. IEEE Commun. Mag. 55(5), 80–87 (2017)

    Article  Google Scholar 

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Code Availability (Software Application or Custom Code)

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Funding

This study was supported by the Fundamental Research Funds for the Central Universities(2020ZDPY0223)

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Authors and Affiliations

  1. IoT/Perception Mine Research Center, China University of Mining and Technology, Xuzhou, 221008, Jiangsu, China

    Kai Zhang, Xiaohu Zhao, Kuncheng Yan & Pengyan Sun

  2. School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221008, Jiangsu, China

    Kai Zhang, Xiaohu Zhao, Kuncheng Yan & Pengyan Sun

  3. Xuhai College, China University of Mining and Technology, Xuzhou, 221008, Jiangsu, China

    You Peng

Authors
  1. Kai Zhang
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  2. Xiaohu Zhao
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  3. You Peng
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  4. Kuncheng Yan
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  5. Pengyan Sun
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Correspondence to Kai Zhang.

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Zhang, K., Zhao, X., Peng, Y. et al. Analysis of Mobile Communication Network Architecture Based on SDN. J Grid Computing 20, 28 (2022). https://doi.org/10.1007/s10723-022-09617-y

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  • DOI: https://doi.org/10.1007/s10723-022-09617-y

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