A Survey and Evaluation of Modern Developments in Smart Network Software Solutions for the Internet of Things

Abstract

The rapid expansion of the Internet of Things (IoT) has created an urgent need for more adaptive, scalable, and intelligent network infrastructures. In response, network softwarization—encompassing technologies such as Software-Defined Networking (SDN), Network Function Virtualization (NFV), and edge computing—has emerged as a key enabler of efficient IoT deployments. This paper presents a comprehensive survey and critical evaluation of recent advances in intelligent network softwarization tailored to IoT environments. We explore how emerging techniques integrate artificial intelligence (AI) and machine learning (ML) to enhance automation, resource optimization, and real-time decision-making in IoT networks. Furthermore, the study categorizes existing approaches based on architecture, functionality, and application domain while highlighting their strengths, limitations, and future research directions. Our findings provide valuable insights for researchers and practitioners aiming to design next-generation IoT systems that are both intelligent and resilient