Self-Evolving Network Intelligence System

Abstract

The Self Evolving Network Intelligence System is an autonomous framework designed to manage, optimize, and secure modern computer networks using Artificial Intelligence and Machine Learning. Traditional network management relies heavily on static configurations, predefined security rules, and manual intervention, which may not respond effectively to changing traffic conditions and emerging network threats. The proposed system integrates Software Defined Networking with Deep Learning and Reinforcement Learning to continuously monitor network traffic, predict congestion, detect anomalous behavior, and optimize network operations. Network telemetry is analyzed using parameters such as bandwidth utilization, latency, packet flow, and anomalous behavior. Based on these observations, the system can dynamically adjust routing policies, allocate network resources, isolate suspicious traffic, and reroute traffic around failed or congested nodes an administrator dashboard provides visibility into network status, detected anomalies, AI decisions, and remediation activities. The proposed framework is intended to reduce manual intervention, improve network availability, optimize resource utilization, and provide adaptive network security. The system can be applied to dynamic environments such as cloud networks, Internet of Things networks, and next generation communication networks.

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