A Comprehensive Survey on Secure, Scalable, and Intelligent Computer Network Architectures for Performance Optimization

The combination of cloud computing, the Internet of Things (IoT), edge computing, and artificial intelligence (AI) technologies has disrupted contemporary computer networks, making the complex interplay of scalability, security, resource management, and performance optimization apprehensive. Some traditional network topologies tend to underperform with sophisticated threats and the growing number of connected devices. To address these challenges, several complex networking paradigms (i.e., Software-Defined Networking (SDN), Network Function Virtualization (NFV), cloud computing, edge computing, machine learning, deep learning, Zero Trust Architecture (ZTA), and Digital Twin Networks) are employed. This survey offers a detailed analysis of the trustworthy, extensible, and intelligent computer network architectures. It delineates how such architectures improve network performance, dependability, and security. This paper organizes the existing paradigms from the standpoint of the architectures, the optimization, and the security. In addition, the main networking technologies are evaluated against scalability, latency, flexibility, and cybersecurity. This survey identifies critical research issues, control of resources, and self-governing networks. Finally, the self-optimizing networks supported by AI, Digital Twin networks, and Zero Trust security are the emerging research avenues covered by this survey.