Hybrid intelligent self-optimizing OBS burst assembly approach for 5G optical networks
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Amit Kumar Garg
Abstract
One networking technology driving the creation of 5G networks is optical burst switching (OBS). High bandwidth low latency flexible resource allocation and cost effectiveness are just a few of its benefits. However, OBS does have some disadvantages. It requires precise network component synchronization and is susceptible to packet loss due to burst contention. This research approach uses a hybrid intelligent method that combines optimization and predictive functions to present a burst assembly strategy for OBS that is customized for 5G optical networks. This strategy seeks to reduce latency and improve overall network performance by dynamically generating bursts based on the networks current state. The best burst assembly parameters are found using an improved optimization technique and adaptive decision-making is supported by a forecasting learning model that predicts future network conditions. In comparison to previous solutions, the computational results show that this novel mechanism has significantly improved throughput and decreased average latency which ultimately lowers the likelihood of blocking in 5G network scenarios.
Acknowledgments
NS-3 Simulation Tool (network tool).
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interests: No conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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