The Disruptions of 5G on Data-driven Technologies and Applications
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Abstract (arXiv)
With 5G on the verge of being adopted as the next mobile network, there is a need to analyze its impact on the landscape of computing and data management. In this paper, we analyze the impact of 5G on both traditional and emerging technologies and project our view on future research challenges and opportunities. With a predicted increase of 10-100x in bandwidth and 5-10x decrease in latency, 5G is expected to be the main enabler for smart cities, smart IoT and efficient healthcare, where machine learning is conducted at the edge. In this context, we investigate how 5G can help the development of federated learning. Network slicing, another key feature of 5G, allows running multiple isolated networks on the same physical infrastructure. However, security remains the main concern in the context of virtualization, multi-tenancy and high device density. Formal verification of 5G networks can be applied to detect security issues in massive virtualized environments. In summary, 5G will make the world even more densely and closely connected. What we have experienced in 4G connectivity will pale in comparison to the vast amounts of possibilities engendered by 5G.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Sep 2019.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 0; 2025: 1.
6 papers.
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- 2025Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environmentscited by 1
- 2022The Metaverse Data Deluge: What Can We Do About It?cited by 0
- 2025Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environments22 Sep 2025
- 2023Federated Continual Learning via Knowledge Fusion: A Survey27 Dec 2023
- 2022Practical Vertical Federated Learning with Unsupervised Representation Learning13 Aug 2022
- 2022The Metaverse Data Deluge: What Can We Do About It?14 Jun 2022
- 2022Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review29 Apr 2022
- 2021Dynamic Network-Assisted D2D-Aided Coded Distributed Learning26 Nov 2021