The Impact of Artificial Intelligence on Adaptive IP Management for Next-Generation Networks

As current networks continue to grow in complexity due to IOT devices, cloud computing, and distributed computing systems, the challenge of dynamically assigning and managing IP addresses has been realized. The traditional measures applied in conventional IP address technology like DHCP and static IP cannot real-time solve IP conflicts hence, the issues will lead to network down times and other security complications. This research looks into how AI techniques and AI, specifically machine learning (ML) can be used in the dynamic management of IP to prevent conflicts. The advanced AI-based framework that has been proposed employs two main classes of learning which are supervised learning and reinforcement learning besides clustering algorithms to forecast IP conflicts, and allocate resources optimally. The outcomes of experiments prove the effectiveness of the proposed AI approach and its applicability for next-generation network management because of increased efficiency of the conflict resolution and the scalability and security of AI.