Tracing the Progression: Networking Applications From Conventional Methods to Incremental AI/ML Integration

The swift progression of networking technologies and the escalating intricacy of contemporary network environments have stimulated a burgeoning interest in utilizing advanced techniques to tackle various networking hurdles. This paper offers an overview of the evolution of applications within networking, tracing the progression of fundamental technologies, methodologies, and approaches over time. Through an examination of existing literature, we scrutinize pivotal works, recent progressions, and emerging patterns in the field, encompassing areas such as network optimization, anomaly detection, security, and automation. Our observations underscore the profound impact of these techniques on networking, facilitating more effective utilization of resources, improved security measures, and heightened adaptability to fluctuating network dynamics. By exploring ongoing trends and deliberating on future avenues of research, this paper furnishes insights into the current landscape of applications within networking and provides guidance for researchers and professionals endeavouring to navigate the complexities of contemporary networking environments.