The paper “Delving into the Intricacies and Nuances of Modern Nested Network Systems” investigates a novel approach to solving the problems inherent in today’s nested network systems. The suggested technique is an all-encompassing strategy for dealing with such complex systems that makes use of Breadth-First Search (BFS), Genetic Algorithms (GAs), and Deep Neural Networks (DNNs). The purpose of this research is to compare the suggested method to six current practices. The scalability, latency, security, load balancing, fault tolerance, energy efficiency, and quality of service of the network, among others, will all be evaluated as part of this strategy. Using these measures, the suggested technique is compared to the state of the art, with numerical results demonstrating its superiority. The use of four distinct kinds of diagrams to display the comparisons further emphasizes the better performance of the suggested approach. The suggested approach is the best option for dealing with the complexity of contemporary multilayer network topologies, as it enhances performance in a broad range of ways. In order to meet the ever-evolving problems presented by such networks, the results highlight the need of adaptive optimization, automation, and cutting-edge learning methods.