Design And Implementation Of Optimization Method For Network Energy Consumption Based On Machine Learning

With the rapid development of the Internet and the increasing number of network users,network energy consumption increases year by year.The optimization of network energy consumption has become one of the hot issues at home and abroad.Collaborative dormancy technology concentrates network traffic to a subset of the network topology through traffic migration and effectively reduces network energy consumption by adjusting idle devices to dormancy.However,this technology can also have an impact on network performance,such as increasing network transmission delay.Therefore,this paper studies a cooperative sleep method which can guarantee the transmission performance and it is of great significance to reduce network energy consumption and improve transmission performance.This paper summarizes the research status and typical methods of network energy consumption optimization technology.Aiming at the combinatorial optimization of cooperative transmission and network energy consumption,a new network energy consumption optimization method based on machine learning is proposed to reduce network energy consumption while considering the transmission performance.This paper models the energy saving routing decision problem as a multi-commodity flow problem and calculates the energy saving routing by using neighborhood search algorithm.And then,the proposed method realizes network traffic migration and idle device dormancy to reduce network energy consumption.Furthermore,a fully connected neural network is introduced to ensure the convergence of the energy saving decision-making process when the input dimension is amplified,so as to realize fast recognition of the sequence of dormant devices.Finally,based on the real network traffic data,the neural network is trained and the proposed method is tested from the aspects of energy saving percentage,transmission time delay and calculation speed.And the simulation results show that the proposed network energy consumption optimization method can optimize the network energy consumption and guarantee the network transmission delay.