Improving Network Layer Performance Using Artificial Intelligence: A Comprehensive Review

Abstract

The burgeoning fields of AI, ML, and ANNs are poised to reshape the very core of how we optimize network performance, with trans-formative impacts on routing, energy efficiency, and even security. This review paper delves into the cutting edge of AI-driven network layer optimization, analyzing leading research across diverse applications like dynamic routing algorithms, energy management, and intelligent anomaly detec- tion. This review explores the burgeoning application of AI and ML in optimizing the network layer,it discuss various techniques of AI and ML to improving TCP/IP network layer in efficiency, resilience, and security. We examine the rise of self-learning routing protocols that predict traffic flows and optimize path selection in real-time, revolutionizing network responsiveness. On the energy front, we explore how AI can analyze network dynamics and intelligently allocate resources, minimizing energy consumption. Security gains under the AI microscope, also in detecting anomalies and thwarting cyber-attacks before they breach the network perimeter.