A simulator for analyzing a network slicing policy with SLA-based performance isolation of slices

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Abstract


Efficient allocation of radio access network (RAN) resources remains an important challenge with the introduction of 5G networks. RAN virtualization and division into logical subnetworks - slices - puts this task into a new perspective. In the paper we present a software tool based on the OMNeT++ platform and developed for performance analysis of a network slicing policy with SLA-based slice performance isolation. The tool is designed using the object-oriented approach, which provides flexibility and extensibility of the simulation model. The paper briefly presents the slicing policy under study and focuses on the simulator’s architecture and design. Numerical results are provided for illustration.


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Introduction Network slicing is a key next-generation networking technology that allows multiple virtual subnetworks to be built over a shared physical infrastructure. The virtual subnetworks are then configured to meet the specific needs of applications, services, devices, customers, or virtual network operators. This approach makes it possible to implement in practice flexible configuration and infrastructure management, which make part of the requirements for new generation networks [1]. This concept allows the infrastructure provider to lease network slices to tenants. These relationships are governed by the Service Level Agreements (SLA). Efficient use of network bandwidth and adherence to the terms of these agreements provides economic benefits to all parties. Guaranteeing slice isolation when allocating RAN radio resources makes the problem of efficient resource allocation even more challenging. The emerging fifth generation (5G) telecommunication networks are en- visioned to offer a large number of end-to-end network services for various applications. These stem not only from traditional mobile services, but also from vertical market segments such as automatic driving, unmanned aerial vehicles, telemedicine, massive Internet of Things (mIoT), etc. To provide services with so different requirements for the quality of service (QoS), it is crucial to be able to implement specific virtual subnetworks by using network slicing, since fourth generation (4G) networks with their one-fits-all paradigm are no longer fitted for the task [2], [3]. In this paper, we propose a simulation model as a reusable, versatile tool for evaluating slicing policies for next-generation network resource sharing. The rest of the article is structured as follows. Section 2 presents the system model. In Section 3 we briefly present the slicing policy under study, which was initially proposed by the authors in [4]. Further, it is considered in terms of queuing theory in Section 4. Section 5 explains the architecture of the simulator. The experimental results are discussed in Section 6. Finally, in Section 7, conclusions are drawn and future work is outlined. System model and notation Following [4], [5], we consider the downlink transmission of a 5G base station (BS) with a virtualized RAN and network slicing. We assume that there are

About the authors

Nikita A. Polyakov

Peoples’ Friendship University of Russia (RUDN University)

Author for correspondence.
Email: goto97@mail.ru
6, Miklukho-Maklaya St., Moscow, 117198, Russian Federation

Bachelor of Science, Master student

Natalia V. Yarkina

Peoples’ Friendship University of Russia (RUDN University)

Email: ksam@sci.pfu.edu.ru
6, Miklukho-Maklaya St., Moscow, 117198, Russian Federation

Candidate of Sciences

Konstantin E. Samouylov

Peoples’ Friendship University of Russia (RUDN University); Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences (FRC CSC RAS)

Email: ksam@sci.pfu.edu.ru
6, Miklukho-Maklaya St., Moscow, 117198, Russian Federation; 44-2, Vavilov St., Moscow, 119333, Russian Federation

Doctor of Technical Sciences, Professor, applied Mathematics & Communications Technology Institute

References

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  3. H. Yu, F. Musumeci, J. Zhang, M. Tornatore, and Y. Ji, “Isolationaware 5G RAN slice mapping over WDM metro-aggregation networks,” Journal of Lightwave Technology, vol. 38, no. 6, pp. 1125-1137, 2020. doi: 10.1109/JLT.2020.2973311.
  4. N. Yarkina, Y. Gaidamaka, L. M. Correia, and K. Samouylov, “An analytical model for 5G network resource sharing with flexible SLA- oriented slice isolation,” Mathematics, vol. 8, 2020. DOI: 10. 3390 / math8071177.
  5. B. Rouzbehani, L. M. Correia, and L. Caeiro, “A service-oriented approach for radio resource management in virtual RANs,” Hindawi Wireless Communications and Mobile Computing, 2018. DOI: 10.1155/ 2018/4163612.
  6. B. Gladkih, Optimization techniques and operations research for computer science bachelors. Part 2. Non-linear and dynamic programming [Metody optimizacii i issledovanie operacij dlya bakalavrov informatiki. CH. 2. Nelinejnoe i dinamicheskoe programmirovanie]. Tomsk: Izd-vo NTL, 2011, in Russian.
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Copyright (c) 2021 Polyakov N.A., Yarkina N.V., Samouylov K.E.

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