Network Slicing for 5G with SDN/NFV: Concepts, Architectures and Challenges
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Abstract (arXiv)
The fifth generation of mobile communications is anticipated to open up innovation opportunities for new industries such as vertical markets. However, these verticals originate myriad use cases with diverging requirements that future 5G networks have to efficiently support. Network slicing may be a natural solution to simultaneously accommodate over a common network infrastructure the wide range of services that vertical-specific use cases will demand. In this article, we present the network slicing concept, with a particular focus on its application to 5G systems. We start by summarizing the key aspects that enable the realization of so-called network slices. Then, we give a brief overview on the SDN architecture proposed by the ONF and show that it provides tools to support slicing. We argue that although such architecture paves the way for network slicing implementation, it lacks some essential capabilities that can be supplied by NFV. Hence, we analyze a proposal from the ETSI to incorporate the capabilities of SDN into the NFV architecture. Additionally, we present an example scenario that combines SDN and NFV technologies to address the realization of network slices. Finally, we summarize the open research issues with the purpose of motivating new advances in this field.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Mar 2017.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 2.
6 papers.
- 2021Generative Adversarial Networks (GANs) in Networking: A Comprehensive Survey & Evaluationcited by 11
- 2021Machine Learning Assisted Security Analysis of 5G-Network-Connected Systemscited by 2
- 2022Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligencecited by 2
- 2021Learning based E2E Energy Efficient in Joint Radio and NFV Resource Allocation for 5G and Beyond Networkscited by 0
- 2026GAN-Enhanced Deep Reinforcement Learning for Semantic-Aware Resource Allocation in 6G Network Slicingcited by 0
- 2026Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Controlcited by 0
- 2026Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Control2 Aug 2026
- 2026GAN-Enhanced Deep Reinforcement Learning for Semantic-Aware Resource Allocation in 6G Network Slicing27 Mar 2026
- 2022Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence27 Jan 2022
- 2021Machine Learning Assisted Security Analysis of 5G-Network-Connected Systems7 Aug 2021
- 2021Learning based E2E Energy Efficient in Joint Radio and NFV Resource Allocation for 5G and Beyond Networks13 Jul 2021
- 2021Generative Adversarial Networks (GANs) in Networking: A Comprehensive Survey & Evaluation10 May 2021