改进的云资源调度自相关匹配数据融合算法  

Fusion Algorithm of Auto Correlation Matching Data Under Modified Cloud Resource Scheduling

作　　者：邢乃若 惠晓滨[1] 

机构地区：[1]空军工程大学装备管理与安全工程学院 [2]解放军94371部队

出　　处：《科技通报》2014年第12期217-219,共3页Bulletin of Science and Technology

摘　　要：提出一种基于自相关匹配滤波和云间相似程度特征提取的云资源调度数据融合算法。设计了基于云资源调度的云计算海量数据处理平台,构建数据融合预处理模型,在云资源调度系统中,设计自相关匹配滤波器,得到融合特征分簇重构空间,对特征进行模式匹配,得到后置处理滤波器的系统函数,实现了对云资源调度自相关匹配数据融合算法的改进。仿真实验表明,该算法能高精度、高平稳地实现云资源调度数据的融合,对云滴数的要求极低,数据处理效果较好,云资源调度执行任务数、云资源调度总任务完成时间、用户满意度等指标优于传统方法,展示了较好的应用价值。In based on self correlation matched filtering and cloud similarity feature extraction, an improved cloud resourcescheduling data fusion algorithm is proposed. Design calculation of mass data processing platform cloud resource schedul-ing based on the cloud, constructing data fusion pretreatment model, in the cloud resource scheduling system, design of selfcorrelation matching filter, get the cluster reconstruction space feature fusion, the characteristics of pattern matching, getthe post processing filter system function. Simulation results show that, the algorithm can achieve high precision, it cansmoothly fuse cloud resource scheduling data, cloud droplet number request is very low, the data processing effect is better,to lay the foundation for effectively improving the cloud resource scheduling performance. The user satisfaction index is su-perior to traditional methods, it has a good application value.

关 键 词：云资源 调度 自相关 数据融合 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]