Resource Allocation of Large-Scale Communication Network based on Machine Learning

With the continuous development of mobile Internet technology, its demand for network performance is also increasing. Although the traditional multi-level structure of network resources enhances the scalability and independence of the network, it cannot be used effectively, nor can it intelligently configure network resources. To this end, this paper explores a new network resource allocation method, namely, a machine learning-based large-scale communication network resource allocation method. This paper first explains the concepts of communication network resource allocation and machine learning, and then proposes the principle of communication network resource allocation based on machine learning. Finally, through experiments, this paper analyzes that the bandwidth utilization rate, data delay and packet loss rate of the communication network resource allocation based on the method in this paper are 78%, 5ms and 0.05%, respectively, and the comprehensive performance is better than other communication network resource allocation methods.