基于小波分析的a-多样性k-匿名大数据自适应延迟调度算法

为提高采用k-匿名模型进行a-多样性大数据延迟调度的自适应性和控制准确性, 提出一种基于小波分析的a-多样性k-匿名大数据自适应延迟调度算法. 首先采用小波分析方法对数据进行去噪处理, 通过去噪数据构建优先级列表控制模型; 然后利用高效时分多址协议设计负载均衡传输的信道模型, 并结合自适应加权控制方法建立调度控制的目标函数, 通过时隙分配进行目标函数的最优化求解, 实现调度算法改进设计. 仿真实验结果表明, 采用该方法进行a-多样性k-匿名大数据调度的自适应均衡性能较好, 数据调度的相对误差较低, 数据的召回率优于传统方法.

a-Diversity k-Anonymity Large Data Adaptive DelayScheduling Algorithm Based on Wavelet Analysis

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.