Network Function Virtualization: State-of-the-art and Research Challenges
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Abstract (arXiv)
Network Function Virtualization (NFV) has drawn significant attention from both industry and academia as an important shift in telecommunication service provisioning. By decoupling Network Functions (NFs) from the physical devices on which they run, NFV has the potential to lead to significant reductions in Operating Expenses (OPEX) and Capital Expenses (CAPEX) and facilitate the deployment of new services with increased agility and faster time-to-value. The NFV paradigm is still in its infancy and there is a large spectrum of opportunities for the research community to develop new architectures, systems and applications, and to evaluate alternatives and trade-offs in developing technologies for its successful deployment. In this paper, after discussing NFV and its relationship with complementary fields of Software Defined Networking (SDN) and cloud computing, we survey the state-of-the-art in NFV, and identify promising research directions in this area. We also overview key NFV projects, standardization efforts, early implementations, use cases and commercial products.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Sep 2015.
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Citing papers per year: 2021: 4; 2022: 1; 2023: 1; 2024: 0; 2025: 1; 2026: 2.
9 papers.
- 2021Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challengescited by 12
- 2021A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placementcited by 5
- 2021Secure Multi-Function Computation with Private Remote Sourcescited by 2
- 2026Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Controlcited by 2
- 2023Collaboration in Immersive Environments: Challenges and Solutionscited by 1
- 2025Dynamic Preference Multi-Objective Reinforcement Learning for Internet Network Managementcited by 1
- 2021Learning based E2E Energy Efficient in Joint Radio and NFV Resource Allocation for 5G and Beyond Networkscited by 0
- 2022A Graph Neural Networks based Framework for Topology-Aware Proactive SLA Management in a Latency Critical NFV Application Use-casecited by 0
- 2026Dynamic Management of a Deep Learning-Based Anomaly Detection System for 5G Networkscited by 0
- 2026Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Control2 Aug 2026
- 2026Dynamic Management of a Deep Learning-Based Anomaly Detection System for 5G Networks21 Jan 2026
- 2025Dynamic Preference Multi-Objective Reinforcement Learning for Internet Network Management16 Jun 2025
- 2023Collaboration in Immersive Environments: Challenges and Solutions1 Nov 2023
- 2022A Graph Neural Networks based Framework for Topology-Aware Proactive SLA Management in a Latency Critical NFV Application Use-case10 Nov 2022
- 2021Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges14 Nov 2021
- 2021Learning based E2E Energy Efficient in Joint Radio and NFV Resource Allocation for 5G and Beyond Networks13 Jul 2021
- 2021Secure Multi-Function Computation with Private Remote Sources17 Jun 2021
- 2021A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placement14 May 2021