标题：H2-RAID: A novel hybrid RAID architecture towards high reliability
作者：Wang T.; Zhang Z.; Zhao M.; Liu K.; Jia Z.; Yang J.; Wu Y.
作者机构：[Wang, T] School of Computer Science and Technology, Shandong University, QingDao, China;[ Zhang, Z] School of Computer Science and Technology, Shando 更多
通讯作者地址：[Jia, Z] School of Computer Science and Technology, Shandong UniversityChina;
来源：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
关键词：Hard disk drive; Hybrid architecture; RAID reliability; Solid state drive
摘要：With the rapid development of storage technology, Solid State Drive (SSD) has received extensive attentions from industry and academia. As a promising alternative of the conventional Hard Disk Drive (HDD), SSD shows its advantages in terms of I/O performance, power consumption and shock resistance. But the natural constraint of write endurance limits the use of SSDs in large-scale storage systems, especially for scenarios with high reliability equirements. The Redundant Arrays of Independent Disks (RAID) technology provides a mechanism of device-level fault tolerance. To guarantee the performance, current RAID strategies usually evenly distributes the I/O requests to all disks. However, different from HDD, the bit error rate (BER) of SSD increases dramatically when it gets older. Therefore, simply introducing RAID technology into SSD array would result in the “correlated SSD failure” problem, that is, all the SSDs in array wear out at approximately the same time, seriously affecting the reliability of the array. In this paper, we propose a Hybrid High reliability RAID architecture named H2 -RAID, which combines SSDs with HDDs to achieve the high-performance of SSDs and the high-reliability of HDDs. To minimize the performance degradation caused by the low-performance HDDs, we design an HDD-aware backup strategy to coalesce the small writes requests. We implement the proposed strategy on the simulator based on Disksim. The experimental results show that we reduce the probability of data loss from 11.31% to 0.02% with only 5% performance loss, in average. © Springer Nature Switzerland AG 2018.