CAJ | 학술논문

重复数据检测技术能够大幅降低数据中心的存储量，节省网络带宽，减少建设和运维成本。为了克服基于内容分块（CDC）方法容易出现超长块的缺点，文章提出了基于极值点分块（EDC）的重复数据检测算法。EDC算法先计算出所有右边界在数据块上下限范围内的滑动窗口中数据的指纹，找出最后一个指纹极值，所对应的滑动窗口结束位置作为数据块的分界点，再计算该数据块的哈希值并判断是否重复块。实验结果表明，EDC算法的重复数据检测率、磁盘利用率分别是CDC算法的1.48倍和1.12倍，改进效果显著。
중복수거검측기술능구대폭강저수거중심적존저량，절성망락대관，감소건설화운유성본。위료극복기우내용분괴（CDC）방법용역출현초장괴적결점，문장제출료기우겁치점분괴（EDC）적중복수거검측산법。EDC산법선계산출소유우변계재수거괴상하한범위내적활동창구중수거적지문，조출최후일개지문겁치，소대응적활동창구결속위치작위수거괴적분계점，재계산해수거괴적합희치병판단시부중복괴。실험결과표명，EDC산법적중복수거검측솔、자반이용솔분별시CDC산법적1.48배화1.12배，개진효과현저。
The duplicate data detection technology can significantly reduce the duplication of data in data centers, save network bandwidth, decrease the cost of construction and maintenance. A duplicate data detection algorithm based on Extremum Defined Chunking(EDC) is proposed to overcome the long segment problem of Content Deifned Chunking(CDC) method. The EDC algorithm ifrst calculates all ifngerprints of the sliding windows that their boundary are within the upper and lower limits of data blocks. The last extremum of all ifngerprints is found out, the corresponding end position of the sliding window become the cut-off point of data block. Then the hash value of the data block is calculated to determine whether it is duplicate block. The experimental results show that ECD algorithm, duplicated data detection rate, disk utilization rate is respectively 1.48 times, 1.12 times of CDC algorithm, the effect is signiifcantly notable.