Environmental and iNet Driven Evolution of Adaptive Agents in Self Organizing Networks
Prabu Ragavendiran · Journal of Computer and Communication Networks · 2025
Self-Organizing Networks (SONs) represent a network design, which enables adaptive agents improve network performance through autonomous actions for self-management while reacting to shifting environmental conditions. The iNet mechanism provides the conceptual framework in this research. This research analyzes agent flexibility in SONs through evaluations of the iNet framework that operates with environmental assessment capabilities. The analysis uses simulated models to simulate agent conduct both with and without evolution in order to gauge how shifting network parameters affect performance indicators consisting of throughput, reaction time and load balancing. Both the agents' ability to adapt their behavior policies and the environmental assessment system jointly result in optimized resource allocation and improved management of tasks and better demand responsiveness. Research results prove that incorporating adaptive evolutionary mechanisms produces superior performance in SONs especially when the networks contain heterogeneous elements. The study introduces breakthrough findings about how evolutionary approaches and awareness of the environment help improve distributed network agents' behavior.