
doi: 10.1109/ccbd.2014.17
The emergence of big data needs more and more storage capacity, and hard disk drive (HDD) plays a very important role in storage supplying. However, because of super paramagnetic effect, the growth of the areal density of HDD will quickly reach the limitation of 1Tb/in2. Shingled magnetic recording (SMR) is one of the most promising technologies to improve the areal density. In this paper, we have evaluated the performance of RAID system composed of SWDs. We have implemented a simulator, referred to as SWDsim, by extending Disksim-4.0 to simulate shingled write disk (SWD). We have proposed Shingle Translation Layer (STL) to SWDsim of which the main functions are address mapping and garbage collection. We describe our design and carry out extensive tests under enterprise, video monitoring and data archiving workloads on SWD-based RAID0/RAID10/RAID5. A set of lessons are extracted applicable to other SWD-based RAID systems. Our experimental results show that SWD-based RAID system has good spatial locality in data updates under read-dominant workloads or write-dominant workloads. And SWD-based RAID system shows nearly the same performance with HDD-based RAID system under read-dominant and sequential write-dominant workloads. However, mainly because of expensive garbage collection operations, SWD-based RAID system always performs worse than traditional HDD-based RAID system under write-dominant workloads with heavy data updates. Our early practice shows that SWDs are not suitable for RAID system deployment for enterprise applications which update data frequently, however, they could be used under read-dominant or sequential write-dominant applications such as cold data storage.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
