Software-Defined Networking (SDN) and Network Function Virtualization (NFV) for Space-Air-Ground-Sea 6G Networks - PHD

The advancement of 6G networks necessitates a holistic approach to global connectivity, integrating terrestrial, aerial, satellite, and maritime systems into a unified space-air-ground-sea (SAGS) network. This convergence demands dynamic network management techniques capable of addressing the challenges posed by heterogeneous infrastructures, variable latency conditions, and resource allocation constraints. SDN and NFV emerge as the pivotal technologies in facilitating flexible, scalable, and adaptive communication architectures, optimizing network control and reducing operational complexities. The deployment of 6G SAGS networks will support critical applications, including industrial IoT, smart city, disaster response, autonomous transportation, and real-time edge computing. The programmability and virtualization capabilities offered by SDN and NFV ensure dynamic network reconfiguration, improved fault tolerance, and efficient resource orchestration, fundamental to the performance and reliability of 6G systems. Unfortunately, traditional SDN and NFV methods struggle to accommodate the multi-domain characteristics of SAGS environments due to their centralization, necessitating a paradigm shift toward scalable distributed frameworks. Moreover, the integration of SDN and NFV in a decentralized SAGS infrastructure presents several challenges: 1) Dynamics and heterogeneity of network environments complicates seamless interoperability between satellite, airborne, terrestrial, and maritime nodes, requiring adaptive communication protocols; 2) Latency variability remains a fundamental constraint, particularly for real-time mission-critical applications; 3) Reliability in distributed control mechanisms is another pressing issue, given the potential for disruptions in high-mobility scenarios. 4) Security vulnerabilities in virtualized environments necessitate robust trust management frameworks, mitigating risks associated with data integrity and cyber threats. Addressing these challenges requires innovative approaches that leverage advanced computational models. Hence, the aim of the proposed research to design novel distributed SDN and NFV protocols for 6G SAGS networks focusing on the following topics: Adaptive AI-driven communication and computing protocols for interoperability enabling i) distributed cross-layer optimization to improve coordination between satellite, airborne, terrestrial, and maritime nodes and ii) leveraging AI, distributed machine learning (ML) and DFL to dynamically adapt to the network conditions. Distributed dynamic latency optimization for real-time applications, considering i) hierarchical multi-controller SDN architectures with centralized and distributed SDN controllers to balance latency and scalability; ii) AI-based network management utilizing ML and DFL for optimized network slicing and resource allocation. Reliability enhancements for distributed control for improved fault tolerance and load balancing with self-healing networks employing AI-based anomaly detection and automated recovery mechanisms. Security and trust management in virtualized environments based on zero-trust security models to enforce strict authentication and access control policies across SDNNFV layers with decentralized identity management, and secure multiparty computations utilizing lightweight cryptographic protocols.