关键词: k-匿名, 大数据, 自适应, 调度, 优先级列表控制

Abstract: In order to improve the adaptability and control accuracy of k-anonymity model for a-diversity large data delay scheduling, we proposed an adaptive delay scheduling algorithm for a-diversity k-anonymity large data based on wavelet analysis. Firstly, wavelet analysis was used to denoise the data, and priority list control model was constructed by denoising data. Secondly, a channel model of load balancing transmission was designed by using efficient time division multiple access protocol, and an objective function of scheduling control was established by combining adaptive weighting control method. The optimal solution of the objective function was achieved by slot allocation to realize the improved design of scheduling algorithm. The simulation results show that the adaptive equilibrium performance of a-diversity k-anonymity large data scheduling using the proposed method is better, the relative error of data scheduling is low, and the recall rate of data is better than the traditional method.

Key words: k-anonymity, large data, adaptive, scheduling, priority list control