A Survey on Traffic Prediction Techniques Using Artificial Intelligence for Communication Networks

Much research effort has been conducted to introduce intelligence into communication networks in order to enhance network performance. Communication networks, both wired and wireless, are ever-expanding as more devices are increasingly connected to the Internet. This survey introduces machine learni...

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Bibliographic Details
Published in:Telecom (Basel) 2021-12, Vol.2 (4), p.518-535
Main Authors: Chen, Aaron, Law, Jeffrey, Aibin, Michal
Format: Article
Language:English
Subjects:
Artificial intelligence
Automation
Big Data
Communication networks
Communications networks
Data analysis
Decision making
Deep learning
Internet of Things
Machine learning
optical networks
Software
traffic prediction
Traffic surveys
Wide area networks
Wireless communications
Wireless networks
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Summary:Much research effort has been conducted to introduce intelligence into communication networks in order to enhance network performance. Communication networks, both wired and wireless, are ever-expanding as more devices are increasingly connected to the Internet. This survey introduces machine learning and the motivations behind it for creating cognitive networks. We then discuss machine learning and statistical techniques to predict future traffic and classify each into short-term or long-term applications. Furthermore, techniques are sub-categorized into their usability in Local or Wide Area Networks. This paper aims to consolidate and present an overview of existing techniques to stimulate further applications in real-world networks.
ISSN:2673-4001
2673-4001
DOI:10.3390/telecom2040029