We use cookies to improve your experience with our site.
孙大为, 常桂然, 高尚, 靳立忠, 王兴伟. 云计算环境中一种实现高可用性的动态数据复制策略[J]. 计算机科学技术学报, 2012, (2): 256-272. DOI: 10.1007/s11390-012-1221-4
引用本文: 孙大为, 常桂然, 高尚, 靳立忠, 王兴伟. 云计算环境中一种实现高可用性的动态数据复制策略[J]. 计算机科学技术学报, 2012, (2): 256-272. DOI: 10.1007/s11390-012-1221-4
Da-Wei Sun, Gui-Ran Chang, Shang Gao, Li-Zhong Jin, Xing-Wei Wang. Modeling a Dynamic Data Replication Strategy to Increase System Availability in Cloud Computing Environments[J]. Journal of Computer Science and Technology, 2012, (2): 256-272. DOI: 10.1007/s11390-012-1221-4
Citation: Da-Wei Sun, Gui-Ran Chang, Shang Gao, Li-Zhong Jin, Xing-Wei Wang. Modeling a Dynamic Data Replication Strategy to Increase System Availability in Cloud Computing Environments[J]. Journal of Computer Science and Technology, 2012, (2): 256-272. DOI: 10.1007/s11390-012-1221-4

云计算环境中一种实现高可用性的动态数据复制策略

Modeling a Dynamic Data Replication Strategy to Increase System Availability in Cloud Computing Environments

  • 摘要: 在云计算环境中错误将以一种常态形式出现,为了实现高可用性,复制热点数据到多个可用站点是一个很好的选择,因为用户可以从距离其最近的站点进行数据访问。然而,在云计算环境中为哪些数据,在什么时候,创建多少副本,并如何放置副本亟待深入研究。本文提出了一种数据副本复制策略。首先,分析和建模了系统可用性和数据副本数目之间的关系。其次,对热点数据进行了量化,当数据的热度超过系统所设置的动态阈值时,将该数据标识为待创建副本的数据。再次,为了满足特定的系统比特效率,为副本确定所需要创建的副本数目,并以一种负载均衡的方式将所创建的副本放置到系统中的恰当位置。最后,设计了一种云计算环境中的动态数据副本复制算法。实验结果分析表明,所提出的数据副本复制策略在仅仅需要少量数据副本的情况下,极大的提高了云计算环境中数据的可用性,满足了系统的高可用要求。

     

    Abstract: Failures are normal rather than exceptional in the cloud computing environments. To improve system avai-lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.

     

/

返回文章
返回