Adaptive Wireless Network Selection Algorithm Based On Mobile Terminal Power

With the rapid development of mobile Internet,the demand of users has also developed from a single call to diversified and diversified business needs.Mainstream wireless network technologies are different in implementation methods,and have advantages and disadvantages in providing services.They cannot be replaced with each other.Therefore,the current wireless network environment is a heterogeneous wireless network environment in which multiple network access technologies and wireless networks coexist.In this case,in order to ensure users' good business experience,reasonable design of wireless network selection algorithm to meet users' business needs has become a hotspot in heterogeneous wireless network research.In this paper,the heterogeneous wireless network selection algorithm was studied,two algorithms are proposed.The first is the wireless network selection algorithm based on terminal remaining power,it will be for the remainder of the mobile terminal power into consideration,the first to use work subjective and objective comprehensive empowerment method(based on FAHP and entropy weight method)to calculate the initial weights,and then adjust the weights according to the terminal remaining power adaptive,finally using DIA(Distance to the ideal Alternative)algorithm sort of candidate networks.Experiments show that the algorithm solves the problem of power consumption weight ladder change,and when the remaining power of the terminal is insufficient,it prefers to choose the network with lower power consumption to save the terminal power.At the same time,it comprehensively considers the power consumption and business demand to avoid the problem that the target network cannot meet the user's business demand.The second algorithm is the TOPSIS(Technique for Order Preference by Similarity to an Ideal Solution)network selection algorithm based on the quadratic moving average.It first uses TOPSIS to calculate the score of the candidate network,and then forecasts the score of the candidate network according to the historical data.Only when both the current score and the predicted score are the best can the network switch be made.Experiments show that the algorithm can effectively reduce the number of ping-pong selection,and the network ratio selected in different business types is basically the same as TOPSIS,reaching the expected goal of the algorithm.