多维场景数据的共享存取优化模型  

The Shared Access Optimization Model on Multidimensional Scene Data

作　　者：李云飞[1] LI Yun-fei(Department of Commerce and Technology/Xijing University, Xi’an 710123, China)

机构地区：[1]西京学院商贸技术系

出　　处：《山东农业大学学报（自然科学版）》2019年第3期429-433,共5页Journal of Shandong Agricultural University：Natural Science Edition

摘　　要：为了提高对多维场景数下不完备日志块状数据的共享存储能力,本文提出一种基于关联规则项引导性融合的多维场景数据下不完备日志块状数据智能存取算法,采用模糊控制方法构建多维场景数下不完备日志块状数据调度控制模型,引入多维场景不完备日志块状数据的自适应调度加权系数,对云存储多维场景不完备日志块状数据采用模糊约束进化方法进行径向寻优,建立一种基于数据挖掘理论的云存储多维场景不完备日志块状数据共享存取数学模型,根据融合系数采用模糊聚类实现自适应寻优,实现对多维场景数下不完备日志块状数据的共享存取。仿真实验表明,采用该算法进行多维场景数下不完备日志块状数据共享存取的准确性较高,吞吐性较好,提高了多维场景不完备日志块状数据调度控制的鲁棒性。In order to improve the sharing and scheduling ability of incomplete log block data on multidimensional scenario, we need to design a shared access optimization model on multidimensional scene data. This paper presented an intelligent access algorithm of incomplete log block data under multidimensional scenario based on the guidance fusion of association rules. Fuzzy control method was used to construct the scheduling control model of incomplete log block data under multidimensional scenario. The adaptive scheduling weighting coefficient of incomplete log block data of multidimensional scene was introduced, and the fuzzy constraint evolution method was used to optimize the incomplete log block data in cloud storage. A mathematical model of cloud storage multidimensional scene incomplete log block data sharing access based on data mining theory was established. The fusion coefficient fuzzy clustering was used to realize adaptive optimization. The shared access of incomplete log block data under multidimensional scenario was realized. The simulation results showed that the proposed algorithm was more accurate and convergent for sharing and accessing incomplete log block data under multidimensional scenario, and improved the robustness of scheduling control of incomplete log block data in multidimensional scene.

关 键 词：多维场景 数据 共享存取 优化模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]