摘要
基于云计算的MAC层数字化信息平台是整合教育信息资源的基础设施,由于在云平台中进行频繁性大数据查询等操作,导致解析引擎中的缓存数据负载压力增大,需要进行缓存数据预取设计。提出一种基于QoS信息特征信息维度匹配的MAC层数字化信息平台解析引擎缓存数据预取算法,对802.11e MAC层数字化信息服务平台进行数据压缩预处理,采用云计算对存放进入缓存的数据对象进行QoS信息特征维度匹配,通过非高斯函数极限分离特性,最大限度对各独立变量进行自相关成分表征,提取QoS信息特征,在MAC层数字化信息服务平台中进行数据传感器分布设计,根据每个段中的数据节点个数,动态分配数据,使系统完成数据的动态存储与访问,得到对解析引擎数据的预取调控函数。仿真实验结果表明,该算法进行MAC层数字化信息平台解析引擎缓存数据预取,数据访问延迟率均小于其它算法,证明了该算法的优越性。
MAC layer of digital information platform is researched based on cloud computing infrastructure integration of educational information resources, due to the frequent data query operation is on the cloud platform, lead to cache the data analysis engine load pressure increases, the need for data cache prefetching design. A parsing engine cache data the pre MAC layer of digital information platform for matching QoS information algorithm is proposed based on the dimension of feature information, the 802.11 e MAC layer of digital information service platform for data compression, using cloud computing to the data objects are stored in the cache in QoS information feature dimension matching, separation properties by non Gauss function limit, the maximum of autocorrelation characterization of components of the the independent variables,the QoS information extraction of features, design of sensor data distribution in the MAC layer of digital information service platform, according to the number of data nodes in each segment, dynamic allocation of data, the system completes the dynamic storage and access to data, the analytical engine data prefetching control function. The simulation results show that,the algorithm of digital information platform MAC layer analytical engine cache data prefetching, data access latency ratio is less than the other algorithms, it proves the superiority of this algorithm.
出处
《科技通报》
北大核心
2015年第2期49-51,共3页
Bulletin of Science and Technology
关键词
数字化信息平台
云计算
引擎
缓存数据
digital information platform
cloud computing
engine
data cache