虛擬機備份系統(tǒng)中存儲空間的優(yōu)化
發(fā)布時間：2018-07-18 08:07
【摘要】：隨著科學技術(shù)的快速發(fā)展，越來越多的企業(yè)或單位開始利用虛擬機搭建數(shù)據(jù)中心來應(yīng)對日益增長的計算需求。然而，隨著數(shù)據(jù)中心虛擬機數(shù)目的不斷增加，單個虛擬機發(fā)生故障從而導致整個數(shù)據(jù)中心失效的概率也隨之增加。目前，虛擬機保護技術(shù)主要包括虛擬機遷移和虛擬機備份，它們都是遷移或備份完整的虛擬磁盤文件，這會消耗大量的存儲資源和網(wǎng)絡(luò)帶寬。因此，提高存儲資源的利用率，是虛擬機保護技術(shù)中必須解決的一個重要問題。 重復(fù)數(shù)據(jù)刪除技術(shù)是一種新型的數(shù)據(jù)縮減技術(shù)，它能夠消除相同數(shù)據(jù)內(nèi)容的文件、數(shù)據(jù)塊或字節(jié)，只保存它們的一個副本。因此，采用基于數(shù)據(jù)段相似性的重復(fù)數(shù)據(jù)刪除解決方案消除虛擬磁盤文件之間的重復(fù)數(shù)據(jù)，不僅可以降低虛擬磁盤文件的存儲空間，而且能夠減少虛擬機的備份窗口。針對重復(fù)數(shù)據(jù)刪除技術(shù)的讀性能下降和指紋匹配問題，，分別采用VmStore和HashDB技術(shù)。VmStore遵循相鄰數(shù)據(jù)相鄰存儲的原則，可以有效緩解重復(fù)數(shù)據(jù)刪除所帶來的讀性能問題。HashDB基于數(shù)據(jù)段的相似性原理，不僅可以提高指紋匹配效率，而且能夠節(jié)約內(nèi)存空間。 對包含有多種虛擬磁盤文件的數(shù)據(jù)集進行了詳細測試。測試結(jié)果表明，變長分塊算法適用于不同虛擬平臺下的虛擬磁盤文件，同一虛擬平臺下的不同虛擬磁盤文件之間宜采用固定長分塊算法，基于數(shù)據(jù)段相似性的重復(fù)數(shù)據(jù)刪除解決方案可以有效地挖掘出重復(fù)數(shù)據(jù)，并且通過采用HashDB和VmStore技術(shù)極大地改善了指紋匹配問題和讀性能問題。
[Abstract]:With the rapid development of science and technology, more and more enterprises or units have begun to use virtual machines to build data centers to cope with increasing computing needs. However, with the increasing number of virtual machines in the data center, the probability of the failure of a single virtual machine and the failure of the whole data center is also increased. Computer protection technology mainly includes virtual machine migration and virtual machine backup, which all migrate or backup complete virtual disk files, which will consume a lot of storage resources and network bandwidth. Therefore, improving the utilization of storage resources is an important problem that must be solved in the virtual machine protection technology.
Duplicated data deleting is a new technique for data reduction, which can eliminate files, blocks, or bytes of the same data content and only save a copy of them. Therefore, duplication of data deletion solutions based on data segment similarity can be used to eliminate the duplication of data between virtual disks and not only reduce virtual magnetism. The storage space of the disk file and the backup window of the virtual machine can be reduced. In view of the decline of read performance and fingerprint matching in repeated data deleting technology, the principle that VmStore and HashDB technology.VmStore follow adjacent data adjacent storage can be used to effectively alleviate the read performance problem of.HashDB based on the number of repeats. According to the principle of similarity, the efficiency of fingerprint matching can not only be improved, but also the memory space can be saved.
The test results show that the variable length block algorithm is suitable for the virtual disk files under different virtual platforms, and the fixed long block algorithm should be used between the different virtual disk files under the same virtual platform, and the repeating data deleting solution based on the similarity of the data segment is used. The case can effectively extract duplicate data, and by using HashDB and VmStore technology, fingerprint matching and reading performance problems are greatly improved.
【學位授予單位】：華中科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TP309.3;TP302
[Abstract]:With the rapid development of science and technology, more and more enterprises or units have begun to use virtual machines to build data centers to cope with increasing computing needs. However, with the increasing number of virtual machines in the data center, the probability of the failure of a single virtual machine and the failure of the whole data center is also increased. Computer protection technology mainly includes virtual machine migration and virtual machine backup, which all migrate or backup complete virtual disk files, which will consume a lot of storage resources and network bandwidth. Therefore, improving the utilization of storage resources is an important problem that must be solved in the virtual machine protection technology.
Duplicated data deleting is a new technique for data reduction, which can eliminate files, blocks, or bytes of the same data content and only save a copy of them. Therefore, duplication of data deletion solutions based on data segment similarity can be used to eliminate the duplication of data between virtual disks and not only reduce virtual magnetism. The storage space of the disk file and the backup window of the virtual machine can be reduced. In view of the decline of read performance and fingerprint matching in repeated data deleting technology, the principle that VmStore and HashDB technology.VmStore follow adjacent data adjacent storage can be used to effectively alleviate the read performance problem of.HashDB based on the number of repeats. According to the principle of similarity, the efficiency of fingerprint matching can not only be improved, but also the memory space can be saved.
The test results show that the variable length block algorithm is suitable for the virtual disk files under different virtual platforms, and the fixed long block algorithm should be used between the different virtual disk files under the same virtual platform, and the repeating data deleting solution based on the similarity of the data segment is used. The case can effectively extract duplicate data, and by using HashDB and VmStore technology, fingerprint matching and reading performance problems are greatly improved.
【學位授予單位】：華中科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TP309.3;TP302
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相關(guān)碩士學位論文 前2條
1 張e
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