HS6: An Efficient H-Code RAID-6 Scaling by Optimizing Data Migrating and Parity Updating
HS6: An Efficient H-Code RAID-6 Scaling by Optimizing Data Migrating and Parity Updating
复制标题
HS6：通过优化数据迁移和奇偶校验更新实现高效的 H 代码 RAID-6 扩展
DOI：
10.1007/s11227-021-03739-y
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发表时间：
2021
影响因子：
3.3
通讯作者：
Xie Ping
中科院分区：
文献类型：
--
作者：
Yuan Zhu;You Xindong;Lv Xueqiang;Li Muyuan;Xie Ping
海量数据导致大型数据中心存储容量不足。这增加了组件损坏和磁盘故障的风险。为了提升数据中心的存储能力，扩展成为最受欢迎的选择之一。与其他RAID级别相比，RAID-6部署广泛，具有卓越的可靠性、可用性和可扩展性。然而，更高的可靠性也意味着昂贵的奇偶校验数据更新成本。针对这一问题，本文提出了一种高效的针对H-Code的RAID-6扩展方案--hs6。HS6的基本思想是通过优化数据迁移和奇偶数据更新来降低总的奇偶数据更新成本并节省总的扩展时间。HS6的特点可以概括为：(1)它利用水平数据迁移来消除水平奇偶数据更新，以及(2)它充分利用原始奇偶数据来降低总的奇偶数据更新成本。数值结果和实验数据分析表明：(1)与轮询、Semi-RR和HCS相比，Hs6的数据迁移率分别降低了76.92%-95.31%、55.56%-84.46%和14.29%-16.67%；(2)在离线情况下，Hs6比轮询、Semi-RR和HCS分别节省了62.05%-76.75%、53.24%-73.94%和3.68%-6.79%的总伸缩时间；在四个工作负载下，Semi-RR在总扩展时间上降低了53.04%-76.41%，而HCS在总扩展时间上降低了0.56%-23.78%；(3)hs6在扩展过程中和扩展后保持了与循环调度、Semi-RR和HCS几乎相同的用户平均响应时间。
Caused by massive data, large-scale data centers suffer from insufficient storage capacity. This increases the risk of component damage and disk failure. To enhance storage capacity of data centers, scaling has turned out to be one of the most popular choices. RAID-6 is deployed extensively that has superior reliability, availability, and scalability compared to other RAID levels. However, higher reliability also means expensive parity data update cost. To address this issue, this paper proposes an efficient RAID-6 scaling scheme, HS6, for H-Code. The basic idea of HS6 is reducing the total parity data update cost and saving the total scaling time by optimizing data migration and parity data update. The properties of HS6 can be summarized as follows: (1) it utilizes horizontal data migration to eliminate the horizontal parity data update, and (2) it makes full use of original parity data to cut down the total parity data update cost. Numerical results and experimental data analysis indicate that: (1) HS6 decreases the data migration rate by 76.92%95.31%, 55.56%84.46%, and 14.29%16.67% compared to Round-Robin, Semi-RR, and HCS, (2) HS6 saves the total scaling time by 62.05%76.75%, 53.24%73.94%, and 3.68%6.79% against Round-Robin, Semi-RR, and HCS, respectively, under offline and outperforms Round-Robin by 59.99%79.02%, Semi-RR by 53.04%76.41%, and HCS by 0.56%23.78% in total scaling time under four workloads, and (3) HS6 maintains almost the same user average response time with Round-Robin, Semi-RR, and HCS during scaling and after scaling.