A Novel Machine Learning Architecture for Traffic Grooming and Resource Optimization in 5G Optical Fronthaul
Mailybayeva A. Jain S. Sidhu J. Vashisht N. Thangarasu N. Goyal S.
July/August 2025John Wiley and Sons Inc
Internet Technology Letters
2025#8Issue 4
The emergence of 5G networks has emerged as innovative solutions for traffic grooming and resource management in optical fronthaul networks. Traditional methods are often incapable of managing the complexity of different traffic patterns, low latencies, and high bandwidth consumption, which leads to suboptimal resource allocation and, consequently, high operating costs. The objective is to develop an innovative machine learning (ML) architecture called Intelligent Multi-Attentive Generative Adversarial Networks (IMAGAN) for maximizing resource utilization and traffic grooming (TG) in 5G optical fronthaul networks. The suggested IMAGAN-based architecture consists of a multi-attentive model for identifying spatiotemporal traffic patterns combined with a generative adversarial model to provide synthetic network scenarios. The findings indicate that the IMAGAN-based architecture enhances the performance of energy management systems in terms of resource utilization ratio, bandwidth utilization ratio, rejection ratio, MAE, and RMSE. The findings of the study offer a strong foundation for further improvements in intelligent 5G network design and management.
5G , intelligent multi-attentive generative adversarial networks (IMAGAN) , machine learning (ML) , network resource allocation , optical fronthaul networks , software-defined test bed , traffic grooming (TG)
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Department of Informatics, Atyrau University Named After Kh. Dosmukhamedov, Atyrau, Kazakhstan
Electronics Engineering, Medi-Caps University, Indore, India
Centre of Research Impact and Outcome, Chitkara University, Rajpura, India
Chitkara Centre for Research and Development, Chitkara University, Baddi, India
Department of Computer Science Engineering, Faculty of Engineering and Technology, JAIN (Deemed-To-Be University), Bangalore, India
Quantum University Research Center, Quantum University, Roorkee, India
Department of Informatics
Electronics Engineering
Centre of Research Impact and Outcome
Chitkara Centre for Research and Development
Department of Computer Science Engineering
Quantum University Research Center
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