Annotated Bibliography Part 2 Research 2022

Running head: ANNOTATED BIBLIOGRAPHY-PART 2
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Annotated Bibliography-Part2
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ANNOTATED BIBLIOGRAPHY-PART 2 2
Annotated Bibliography-Part 2
Walia, J. S., Hämmäinen, H., Kilkki, K., & Yrjölä, S. (2019). 5G network slicing strategies for a
smart factory. Computers in Industry, 111, 108–120.
The 5G wireless system is going to improve the flexibility and service quality in factories
through network slicing. Factories are becoming independent of networking, but the current
networking does not give the full potential compared to the 5G wireless networking. This
research show an illustration of how 5G network slicing strategies for a smart factory can
improve productivity and efficiency. Network slicing uses the same physical network to create
logically separated use case-specific virtual networks. Well-defined feasible management models
and strategies are vital to the success of network slicing, even in situations where other qualities
of service and resource reservation technologies have failed. The use of the 5G network
specification will ensure that value networks, network actors, and multiple network domains are
included in the strategy. This will revolutionize the factory sector soon.
Moysen, J., & Giupponi, L. (2018). From 4G to 5G: Self-organized network management meets
machine learning. Computer Communications, 129, 248–268
The 5G network system will change self-organization in the cellular networks soon. Self-
organizing networks (SONs) play a crucial role in the improvement of operation, administration,
and management (OAM) activities. Self-organizing systems aim to reduce the installation cost
and management of 4g and future 5G networks. This can be achieved through the development
of the capability of the SONs to configure, optimize, and heal itself. The 5G network system
management requires the autonomous management of the SONs to be extended to end network.
To achieve this, machine learning technology has been identified as the most appropriate tool to