The Disruptions of 5G on Data-Driven Technologies and Applications

【Author】 Loghin, Dumitrel; Cai, Shaofeng; Chen, Gang; Tien Tuan Anh Dinh; Fan, Feiyi; Lin, Qian; Ng, Janice; Ooi, Beng Chin; Sun, Xutao; Quang-Trung Ta; Wang, Wei; Xiao, Xiaokui; Yang, Yang; Zhang, Meihui; Zhang, Zhonghua

【Source】IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

【影响因子】9.235

【Abstract】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.

【Keywords】5G mobile communication; database systems; network slicing; Internet of Things; edge computing; federated learning; data privacy; security management

【发表时间】2020 1-Jun

【收录时间】2022-01-02

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