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Enhancing network routing protocols is critical for improving network effectiveness and flexibility. The integration of machine learning (ML) in routing processes offers exciting possibilities for optimization. This paper presents how ML-based approaches can improve network routing by optimizing parameters such as latency, throughput, and energy consumption. Results indicate that ML-based systems outperform conventional approaches in most cases, providing significant advantages in terms of dynamic adaptability and efficiency.

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The Optimization of Network Routing Protocols Using Machine Learning Techniques: Opportunities and Challenges

  • 会议论文

  • 发表日期：

    2025年

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  • Aqeel Luaibi Challoob,
  • Anwer Jabbar Hasan,
  • Abbas Abd Alhussein Haddad

摘要

Enhancing network routing protocols is critical for improving network effectiveness and flexibility. The integration of machine learning (ML) in routing processes offers exciting possibilities for optimization. This paper presents how ML-based approaches can improve network routing by optimizing parameters such as latency, throughput, and energy consumption. Results indicate that ML-based systems outperform conventional approaches in most cases, providing significant advantages in terms of dynamic adaptability and efficiency.