The healthcare sector is confronted with challenges in managing the increasing volume of medical data. Traditional IP-based networks struggle to meet the requirements of modern healthcare applications. Integrating Software-Defined Networking (SDN) and Named Data Networking (NDN) is investigated to address these challenges. The combination of SDN’s centralized network control and NDN’s content-centric approach can enhance the performance, security, and flexibility of healthcare networks. Simulations using the Abilene network topology reveal that the SDN/NDN integration leads to significant improvements. Latency is reduced by up to 50%, bandwidth utilization improves by approximately 55%, and packet loss is reduced to 1%. These findings suggest that the SDN/NDN integration offers a promising solution for next-generation healthcare networking, capable of meeting the growing demands of data-intensive medical applications. Challenges in implementing this integrated approach and future research directions, including machine learning-based optimizations and healthcare-specific NDN naming schemes, are also discussed.

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Software-Defined Named Data Networking for Efficient Healthcare Content Distribution

  • Yassine Sembati,
  • Najib Naja,
  • Abdellah Jamali

摘要

The healthcare sector is confronted with challenges in managing the increasing volume of medical data. Traditional IP-based networks struggle to meet the requirements of modern healthcare applications. Integrating Software-Defined Networking (SDN) and Named Data Networking (NDN) is investigated to address these challenges. The combination of SDN’s centralized network control and NDN’s content-centric approach can enhance the performance, security, and flexibility of healthcare networks. Simulations using the Abilene network topology reveal that the SDN/NDN integration leads to significant improvements. Latency is reduced by up to 50%, bandwidth utilization improves by approximately 55%, and packet loss is reduced to 1%. These findings suggest that the SDN/NDN integration offers a promising solution for next-generation healthcare networking, capable of meeting the growing demands of data-intensive medical applications. Challenges in implementing this integrated approach and future research directions, including machine learning-based optimizations and healthcare-specific NDN naming schemes, are also discussed.