NAND flash memory has become an essential storage medium for various mobile devices, but it has some idiosyncrasies, such as out-of-place updates and bulk erase operations, which impair the I/O performance of those devices. In particular, the random write performance is strongly influenced by the overhead of a Flash Translation Layer (FTL) that hides the idiosyncrasies of NAND flash memory. To reduce the FTL overhead, operating systems need to be adapted for FTL, but widely used mobile operating systems still mainly adopt algorithms designed for traditional hard disk drives. Although there have been recent studies on rearranging write patterns into a sequential form in the operating system, these approaches fail to produce sequential write patterns under complicated workloads, and FTL still suffers from significant garbage collection overhead. If the operating system can be made aware of the write patterns that FTL requires, the overhead can be alleviated even under random write workloads. In this paper, we propose a system-wide cooperative optimization scheme, where the operating system communicates with the underlying FTL and generates write patterns that FTL can exploit to reduce the overhead. The proposed scheme was implemented on a real mobile device, and the experimental results show that the proposed scheme constantly improves performance under diverse workloads.

A very promising approach for using NAND flash memory as a storage medium is a flash file system. In order to design a higher-performance flash file system, two issues should be considered carefully. One issue is the design of an efficient index structure that contains the locations of both files and data in the flash memory. For large-capacity storage, the index structure must be stored in the flash memory to realize low memory consumption; however, this may degrade the system performance. The other issue is the design of a novel garbage collection (GC) scheme that reclaims obsolete pages. This scheme can induce considerable additional read and write operations while identifying and migrating valid pages. In this article, we present a novel flash file system that has the following features: ( i ) a lightweight index structure that introduces the hybrid indexing scheme and intra-inode index logging , and ( ii ) an efficient GC scheme that adopts a dirty list with an on-demand GC approach as well as fine-grained data separation and erase-unit data allocation . We implemented FlashLight in a Linux OS with kernel version 2.6.21 on an embedded device. The experimental results obtained using several benchmark programs confirm that FlashLight improves the performance by up to 27.4% over UBIFS by alleviating index management and GC overheads by up to 33.8%.

Recently, NAND flash-based Solid State Drives (SSDs) have been rapidly adopted in laptops, desktops, and server storage systems because their performance is superior to that of traditional magnetic disks. However, NAND flash memory has some limitations such as out-of-place updates, bulk erase operations, and a limited number of write operations. To alleviate these unfavorable characteristics, various techniques for improving internal software and hardware components have been devised. In particular, the internal device cache of SSDs has a significant impact on the performance. The device cache is used for two main purposes: to absorb frequent read/write requests and to store logical-to-physical address mapping information. In the device cache, we observed that the optimal ratio of the data buffering and the address mapping space changes according to workload characteristics. To achieve optimal performance in SSDs, the device cache should be appropriately partitioned between the two main purposes. In this paper, we propose an adaptive partitioning scheme, which is based on a ghost caching mechanism, to adaptively tune the ratio of the buffering and the mapping space in the device cache according to the workload characteristics. The simulation results demonstrate that the performance of the proposed scheme approximates the best performance.

Solid State Disks (SSDs) are superior to magnetic disks from a performance point of view due to the favorable features of NAND flash memory. Furthermore, thanks to improvement on flash memory density and adopting a multi-chip architecture, SSDs replace magnetic disks rapidly. Most previous studies have been conducted for enhancing the performance of SSDs, but these studies have been worked on the assumption that the operation unit of a host interface is the same as the operation unit of NAND flash memory, where it is needless to give consideration to partially-filled pages. In this paper, we analyze the overhead caused by the partially-filled pages, and propose a buffer replacement algorithm exploiting multi-chip parallelism to enhance the write performance. Our simulation results show that the proposed algorithm improves the write performance by up to 30% over existing approaches.

It is an important issue to reduce the power consumption of a hard disk that takes a large amount of computer systempsilas power. As a new trend, an NV cache is used to make a disk spin down longer by servicing read/write requests instead of the disk. During the spin-down periods, write requests can be simply handled by write buffering, but read requests are still the main cause of initiating spin-ups because of a low hit ratio in the NV cache. Even when there is no user activity, read requests can be frequently generated by running applications and system services, hindering the spin-down. In this paper, we propose new NV cache policies: active write caching to reduce or to delay spin-ups caused by read misses during spin-down periods and a read miss-based spin-down algorithm to extend the spin-down periods, exploiting the NV cache effectively. Our policies reduce the power consumption of a hard disk by up to 50.1% with a 512 MB NV cache, compared with preceding approaches.

NAND flash memory becomes one of the most popular storage for portable embedded systems. Although many flash-aware file systems, such as JFFS2 and YAFFS2, were proposed, the large memory consumption and the long mount delay have been serious obstacles for large-capacity NAND flash memory. In this paper, we present a new flash-aware file system called DFFS (direct flash file system) which fetches only the needed metadata on demand from flash memory. In addition, DFFS employs two novel metadata management schemes, inode embedding scheme and hybrid inode indexing scheme, to improve the performance of metadata operations. Comprehensive evaluation results using microbench- mark, postmark, and Linux kernel compilation trace, show that DFFS has comparable performance to JFFS2 and YAFFS2, while achieving a small memory footprint and instant mount time.