MODELING AND PERFORMANCE EVALUATION OF SELF-REGULATING NETWORK ARCHITECTURES

Abstract

This work presents the modeling and performance evaluation of self-regulating network architectures based on distributed control and adaptive feedback mechanisms. Unlike traditional centralized systems, the proposed approach enables network nodes to autonomously manage traffic, optimize resource allocation, and respond to dynamic conditions.

A simulation-based framework is used to analyze key performance metrics, including latency, throughput, and reliability. The results demonstrate improved efficiency, scalability, and stability compared to conventional architectures.

These findings highlight the effectiveness of self-regulation in enhancing network performance and support its potential application in next-generation communication systems.