Application research of Bayesian optimization algorithm in DHCPv6 stateful allocation

This paper studies the application of the Bayesian optimization algorithm in DHCPv6 stateful allocation, addressing the efficiency issues of traditional allocation strategies in high-load scenarios. By constructing a simulation platform, simulating different network load environments, and validating optimization effects in a real network, the experimental results show that the Bayesian optimization algorithm significantly improves network response speed and address allocation success rates, particularly excelling under high-load conditions. This research provides an important reference for further optimization of DHCPv6 networks and verifies the practical value of the algorithm.