5G cloud computing networks are capable of supporting a wide range of applications and services with high performance, low latency and scalability. By employing Artificial Intelligence (AI) based machine learning models, 5G cloud computing networks are able to improve the overall performance and reduce the latency of the network. An AI based machine learning model can anticipate potential network performance, detect and predict network incidents as they happen, and recommend changes in network configuration and parameters to improve the latency. AI models can also be used to optimize routing of traffic by leveraging historical network data and predicting network traffic. Additionally, AI models can be used to manage dynamic spectrum allocation within 5G cloud networks, further improving the latency and throughput of the network. Further, AI enabled automation can help to reduce the amount of manual intervention by allowing for intelligent configurations changes, reducing latency and improving the overall performance of the network.
M Ramkumar, R Karthick, A Jeyashree
Knowledge Institute of Technology, India
5G, Cloud Computing, AI, Machine Learning, Configuration
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| Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 4 , Issue: 2 , Pages: 431 - 435 )
Date of Publication :
March 2023
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