Optimizing Data Transmission in IoT Networks Using Advanced Techniques - Abdulmajeed, Hazem H.;Hefny, Hesham A.;Al-Sawy, Assem A.
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In the expanding landscape of IoT networks, multimedia applications such as online conferencing face significant challenges in maintaining Quality of Service (QoS), including delay, data loss, and costs. This study introduces a multicast routing algorithm based on the Hopfield Neural Network (HNN) to address these QoS issues. Unlike traditional methods, which struggle with increasing data and network complexity, the HNN-based approach effectively adapts to dynamic network topologies to optimize data transmission. The proposed algorithm outperforms conventional techniques, improving overall…mehr

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Produktbeschreibung
In the expanding landscape of IoT networks, multimedia applications such as online conferencing face significant challenges in maintaining Quality of Service (QoS), including delay, data loss, and costs. This study introduces a multicast routing algorithm based on the Hopfield Neural Network (HNN) to address these QoS issues. Unlike traditional methods, which struggle with increasing data and network complexity, the HNN-based approach effectively adapts to dynamic network topologies to optimize data transmission. The proposed algorithm outperforms conventional techniques, improving overall network performance and reliability by efficiently managing QoS constraints and enhancing data integrity.
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Autorenporträt
Hazem H. Abdulmajeed, MSc, focuses on deep learning and IoT applications.Hesham A. Hefny, Ph.D., Professor at Cairo University's FGSSR, specializes in computational intelligence and data mining, has over 180 publications. Assem Al-sawy, Ph.D., former Lecturer and data science leader, now researcher at TU Dublin.