科技通报
科技通報
과기통보
BULLETIN OF SCIENCE AND TECHNOLOGY
2015年
8期
132-134
,共3页
QoS维度%信息服务云平台%资源调度
QoS維度%信息服務雲平檯%資源調度
QoS유도%신식복무운평태%자원조도
QoS dimensions%Information service cloud platform%Resource scheduling
对数字化信息服务云平台的资源准确置换可以提高云平台的数据预取和资源调度能力.传统方法中对信息服务云平台的资源置换采用边缘逆理论并行查询置换算法,不能满足多媒体数据传输的QoS需求.提出一种基于QoS维度分箱的数字化信息服务云平台资源置换算法,以全局度量为中心节点,进行溯源处理,采用QoS维度分箱的信息特征维度匹配,将乘性噪声相对稳定的一段时间称为一个时隙,实现数字化信息服务云平台资源置换算法改进.仿真表明,该算法通过资源置换处理,提高信息检索的定位准确率,减少资源分配的运行时间,提高云平台的资源调度分配性能.
對數字化信息服務雲平檯的資源準確置換可以提高雲平檯的數據預取和資源調度能力.傳統方法中對信息服務雲平檯的資源置換採用邊緣逆理論併行查詢置換算法,不能滿足多媒體數據傳輸的QoS需求.提齣一種基于QoS維度分箱的數字化信息服務雲平檯資源置換算法,以全跼度量為中心節點,進行溯源處理,採用QoS維度分箱的信息特徵維度匹配,將乘性譟聲相對穩定的一段時間稱為一箇時隙,實現數字化信息服務雲平檯資源置換算法改進.倣真錶明,該算法通過資源置換處理,提高信息檢索的定位準確率,減少資源分配的運行時間,提高雲平檯的資源調度分配性能.
대수자화신식복무운평태적자원준학치환가이제고운평태적수거예취화자원조도능력.전통방법중대신식복무운평태적자원치환채용변연역이론병행사순치환산법,불능만족다매체수거전수적QoS수구.제출일충기우QoS유도분상적수자화신식복무운평태자원치환산법,이전국도량위중심절점,진행소원처리,채용QoS유도분상적신식특정유도필배,장승성조성상대은정적일단시간칭위일개시극,실현수자화신식복무운평태자원치환산법개진.방진표명,해산법통과자원치환처리,제고신식검색적정위준학솔,감소자원분배적운행시간,제고운평태적자원조도분배성능.
Accurate resources displacement of the digital information service cloud platform can improve the data prefetch-ing of cloud platform and resource scheduling ability. The traditional methods information service platform use edge inverse theory of parallel query replacement algorithm for resources displacement of the digital information service cloud platform, thus cannot satisfy the QoS requirements of multimedia data transmission. In this paper purposes a digital information ser-vice cloud platform resources replacement algorithm based on QoS dimensions box. According to the separation theorem of autocorrelation function limit, builds a cache replacement function. back processing. Using the information characteristics of QoS dimension box match dimension, the relatively stable period of multiplicative noise is called a time slot, realize the digital information service cloud platform resources replacement algorithm improvement. Simulation show that the proposed algorithm through resource replacement treatment, improves the positioning accuracy of information retrieval, reduces the running time of resources allocation, improves the cloud platform performance of resource distribution and scheduling.