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夏亚楠, 王勇. Ceph 存储系统中节点的容错选择算法[J]. 桂林电子科技大学学报, 2022, 42(5): 384-390.
引用本文: 夏亚楠, 王勇. Ceph 存储系统中节点的容错选择算法[J]. 桂林电子科技大学学报, 2022, 42(5): 384-390.
XIA Yanan, WANG Yong. A fault tolerant nodes selection algorithm in Ceph storage system[J]. Journal of Guilin University of Electronic Technology, 2022, 42(5): 384-390.
Citation: XIA Yanan, WANG Yong. A fault tolerant nodes selection algorithm in Ceph storage system[J]. Journal of Guilin University of Electronic Technology, 2022, 42(5): 384-390.

Ceph 存储系统中节点的容错选择算法

A fault tolerant nodes selection algorithm in Ceph storage system

  • 摘要: Ceph分布式系统中的数据分布算法仅将容量作为选择存储节点的标准,并未考虑存储节点的网络状态和节点负载。在副本模式下,当三副本中有存储节点并需要修复时,过高的节点负载或者网络负载会导致较大的节点修复时延。针对这个问题,给出了一种基于Ceph的节点容错选择(FTNSC)算法。首先利用软件定义网络技术获得实时的网络状态和节点负载信息,作为节点选择方法的数据支撑;然后建立综合考虑节点负载信息的多属性决策数学模型来确定主存储节点位置;最后通过人工蜂群算法根据与主存储节点之间的网络状态和节点性能得到最优次存储节点。实验结果表明,与现有的CRUSH算法相比,该算法在提高数据存储节点性能的同时,将失效数据的修复时延减少2%~29.7%。

     

    Abstract: The data distribution algorithm in Ceph distributed system only takes the capacity as the standard for selecting storage nodes, and does not consider the network state and node load of storage nodes. In the replica mode, when a storage node in the three replicas needs to be repaired, too high node load or network load will lead to a large node repair delay. To solve this problem, a fault-tolerant node selection algorithm based on Ceph (FTNSC) is proposed. Firstly, the software defined network technology is used to obtain the real-time network state and node load information as the data support of the node selection method; Then, a multi-attribute decision-making mathematical model considering the node load information is established to determine the location of the primary storage node; Finally, the artificial bee colony algorithm is used to obtain the optimal secondary storage node according to the network state and node performance with the primary storage node. Experimental results show that compared with the existing methods, the proposed method can improve the performance of data storage nodes and reduce the data repair delay by 2%-29.7%.

     

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