Guest Editors
Assist. Prof. Mangal Sain
Email: mangalsain@gdsu.dongseo.ac.kr
Affiliation: Division of Information and Computer Engineering, Dongseo University, Busan, Republic of Korea
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Research Interests: cloud computing, network security, wireless sensor networks, IoT, deep learning, smart healthcare, AI
Assist. Prof. Kueh Lee Hui
Email: leehkueh@dau.ac.kr
Affiliation: Department of Electrical Engineering, Dong-A University, Busan, Republic of Korea
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Research Interests: artificial intelligence, machine learning, intelligent control, cyber-physical systems, energy systems, and battery assessment for electric vehicles
Summary
Software-Defined Networking (SDN) has revolutionized the design and management of modern communication infrastructures by decoupling the control plane from the data plane, thereby enabling centralized programmability and dynamic control. However, the growing complexity, scale, and heterogeneity of emerging network paradigms—such as the Internet of Things (IoT), edge–cloud ecosystems, and 5G/6G infrastructures—introduce new challenges related to scalability, adaptability, security, and performance optimization. Artificial Intelligence (AI) and Machine Learning (ML) are now key enablers in addressing these challenges. By embedding intelligence into SDN architectures, AI-driven approaches can enhance predictive analytics, autonomous decision-making, and adaptive network orchestration. Such integration paves the way for efficient traffic engineering, proactive fault management, intelligent routing, optimized resource utilization, and resilient network security.
This Special Issue invites original research contributions and comprehensive reviews that investigate the convergence of AI and SDN. The emphasis is on innovative computational models, learning-based algorithms, and real-world applications that advance intelligent networking for next-generation computing environments.
We welcome submissions from researchers and practitioners aiming to shape the future of intelligent, adaptive, and secure network systems through the synergy of AI and SDN.
Topics of Interest:
· AI- and machine learning–based SDN architectures and control frameworks
· Intelligent traffic engineering and flow scheduling using SDN
· AI-driven SDN solutions for Internet of Things (IoT) networks
· Secure SDN architectures using AI and data-driven techniques
· Intrusion detection, anomaly detection, and attack mitigation in SDN environments
· Blockchain-assisted secure and trustworthy SDN systems
· Performance modeling, simulation, and analytical evaluation of AI-enabled SDN
· Intelligent SDN applications for smart cities, smart healthcare, and cyber-physical systems
Keywords
software defined networking (SDN), artificial intelligence–enabled networking, machine learning and deep learning, intelligent traffic engineering,edge and IoT network management, SDN security and intrusion detection, network optimization and metaheuristics, performance modeling and analysis
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