组合盘中结合访问次数与能量代价的文件缓存替换策略

如何有效地降低存储子系统能耗是近几年研究的热点议题。新型非易失、抗震、低功耗闪存及固态盘的出现给存储子系统节能带来了新的机会。但其每单位价格昂贵,目前难以替代硬盘的角色。结合硬盘和固态盘的优势,本文采用组合盘(由硬盘和固态盘组成)节能。结合文件访问次数和能量代价,我们提出了改进的文件缓存替换策略FEBR(Frequency&Energy-based replacement)。实验采用两个真实办公用户数据,结果表明组合盘方案是可行的,节能百分比可达70%～80%;与经典替换算法、最新较好的ARC算法以及理想最优页面OPT算法进行了详细比较,FEBR优于其它策略。     

基于随机游走的大容量固态硬盘磨损均衡算法

基于闪存的大容量固态硬盘(SSD)能够在未来取代磁盘.它有很多优点,包括非易失性、低能耗、抗震性强等.然而,基于NAND闪存的存储块自身存在有限的擦除重写次数的问题一直影响着它的广泛应用.当闪存芯片达到擦除重写的限制次数后,存储块上的数据就会变得不可靠.目前研究者们已经提出了一些磨损均衡算法来解决这个问题.但当固态硬盘的存储容量不断增大后,这些算法需要越来越多的内存容量来保证运行.文中提出一种基于随机游走的磨损均衡算法来应用在大容量的固态硬盘上,该算法能够很大程度地减少内存消耗.实验表明所需内存容量仅为BET算法的15.6%,与此同时磨损均衡的性能并没有降低.     

Chameleon: A High Performance Flash/FRAM Hybrid Solid State Disk Architecture

Flash memory solid state disk (SSD) is gaining popularity and replacing hard disk drive (HDD) in mobile computing systems such as ultra mobile PCs (UMPCs) and notebook PCs because of lower power consumption, faster random access, and higher shock resistance. One of the key challenges in designing a high-performance flash memory SSD is an efficient handling of small random writes to non-volatile data whose performance suffers from the inherent limitation of flash memory that prohibits in-place update. In this paper, we propose a high performance Flash/FRAM hybrid SSD architecture called Chameleon. In Chameleon, metadata used by the flash translation layer (FTL), a software layer in the flash memory SSD, is maintained in a small FRAM since this metadata is a target of intensive small random writes, whereas the bulk data is kept in the flash memory. Performance evaluation based on an FPGA implementation of the Chameleon architecture shows that the use of FRAM in Chameleon improves the performance by 21.3%. The results also show that even for bulk data that cannot be maintained in FRAM because of the size limitation, the use of fine-grained write buffering is critically important because of the inability of flash memory to perform in-place update.     

EED: Energy Efficient Disk drive architecture

Energy efficiency has become one of the most important challenges in designing future computing systems, and the storage system is one of the largest energy consumers within them. This paper proposes an Energy Efficient Disk (EED) drive architecture which integrates a relatively small-sized NAND flash memory into a traditional disk drive to explore the impact of the flash memory on the performance and energy consumption of the disk. The EED monitors data access patterns and moves the frequently accessed data from the magnetic disk to the flash memory. Due to the data migration, most of the data accesses can be satisfied with the flash memory, which extends the idle period of the disk drive and enables the disk drive to stay in a low power state for an extended period of time. Because flash memory consumes considerably less energy and the read access is much faster than a magnetic disk, the EED can save significant amounts of energy while reducing the average response time. Real trace driven simulations are employed to validate the proposed disk drive architecture. An energy coefficient, which is the product of the average response time and the average energy consumption, is proposed as a performance metric to measure the EED. The simulation results, along with the energy coefficient, show that the EED can achieve an 89.11% energy consumption reduction and a 2.04% average response time reduction with cello99 trace, a 7.5% energy consumption reduction and a 45.15% average response time reduction with cello96 trace, and a 20.06% energy consumption reduction and a 6.02% average response time reduction with TPC-D trace, respectively. Traditionally, energy conservation and performance improvement are contradictory. The EED strikes a good balance between conserving energy and improving performance.     

一种闪存敏感的多级缓存管理方法

基于闪存的固态硬盘(solid state driver,简称SSD)已经广泛应用于各种移动设备、PC机和服务器.与磁盘相比,尽管SSD具有数据存取速度高、抗震、低功耗等优良特性,但SSD自身也存在读写不对称、价格昂贵等不利因素,这使得SSD 短期内不会完全取代磁盘.将SSD和磁盘组合构建混合系统,可以发挥不同的硬件特性,提升系统性能.基于 MLC 型 SSD 和 SLC 型 SSD 之间的特性差异,提出了一种闪存敏感的多级缓存管理策略——FAMC.FAMC将SSD用在内存和磁盘之间作扩展缓存,针对数据库系统、文件管理中数据访问的特点,有选择地将内存牺牲页缓存到不同类型的SSD.FAMC同时考虑写请求模式和负载类型对系统性能的影响,设计实现对SSD友好的数据管理策略.此外,FAMC基于不同的数据置换代价提出了适用于SSD的缓冲区管理算法.基于多级缓存存储系统对FAMC的性能进行了评测,实验结果表明,FAMC可以大幅度降低系统响应时间,减少磁盘I/O.     

Buffer flush and address mapping scheme for flash memory solid-state disk

The flash memory solid-state disk (SSD) is emerging as a killer application for NAND flash memory due to its high performance and low power consumption. To attain high write performance, recent SSDs use an internal SDRAM write buffer and parallel architecture that uses interleaving techniques. In such architecture, coarse-grained address mapping called superblock mapping is inevitably used to exploit the parallel architecture. However, superblock mapping shows poor performance for random write requests. In this paper, we propose a novel victim block selection policy for the write buffer considering the parallel architecture of SSD. We also propose a multi-level address mapping scheme that supports small-sized write requests while utilizing the parallel architecture. Experimental results show that the proposed scheme improves the I/O performance of SSD by up to 64% compared to the existing technique.     

Vertical partitioning for flash and HDD database systems

Recent advances in flash memory technology have greatly enhanced the capability of flash memory to address the I/O bottleneck problem. Flash memory has exceptional I/O performance compared to the hard disk drive (HDD). The superiority of flash memory is especially visible when dealing with random read patterns. Even though the cost of flash memory is higher than that of HDD storage, the popularity of flash memory is increasing at such a pace that it is becoming a common addition to the average computer. Recently, flash memory has been made into larger devices called solid state drives (SSDs). Although these devices can offer capacities comparable to HDDs, they are considerably more expensive per byte.Our research aims to increase the I/O performance of database systems by using a small amount of flash memory alongside HDD storage. The system uses a fully vertically partitioned storage structure where each column is stored separately on either the HDD or SSD. Our approach is to assign the columns into the SSD which will benefit the most from the characteristics of flash memory. We prove this problem is NP-complete and propose an optimal dynamic programming solution and a faster greedy heuristic solution.A system simulator has been implemented and experiments show that the overall I/O costs can be greatly reduced using only a limited amount of flash memory. The results show the greedy heuristic solution performed similarly to the more expensive dynamic programming solution for the situations tested.     

A hybrid filesystem for hard disk drives in tandem with flash memory

The traditional hard disk drive (HDD) is often a bottleneck in the overall performance of modern computer systems. With the development of solid state drives (SSD) based on flash memory, new possibilities are available to improve secondary storage performance. In this work, we propose a new hybrid SSD–HDD storage system and a selection of algorithms designed to assign pages across an HDD and an SSD to optimise I/O performance. The hybrid system combines the advantages of the SSD’s fast random seek speed with the sequential access speed and large storage capacity of the HDD to produce significantly improved performance in a variety of situations. We further improve performance by allowing concurrent access across the two types of storage devices. We show the drive assignment problem is NP-complete and accordingly propose effective heuristic solutions. Extensive experiments using both synthetic and real data sets show our system with a small SSD can outperform a striped dual HDD and remain competitive with a dual SSD.     

面向闪存的树型索引综述

随着闪存技术的不断成熟,基于闪存的固态硬盘（solid state drive,SSD）迅速发展。然而,SSD具有不同于磁盘的特性,使得传统基于磁盘设计的索引不适用于闪存环境,因此面向闪存索引机制的研究与优化迅速开展。通过对目前闪存索引的广泛调研,从索引更新策略的角度,分析了它们的优缺点,旨在为SSD算法设计和索引开发提供系统的、有价值的参考。最后讨论了该领域未来的发展趋势和新的研究方向。     

A hybrid flash translation layer design for SLC-MLC flash memory based multibank solid state disk

This paper presents the design of a NAND flash based solid state disk (SSD), which can support various storage access patterns commonly observed in a PC environment. It is based on a hybrid model of high-performance SLC (single-level cell) NAND and low cost MLC (multi-level cell) NAND flash memories. Typically, SLC NAND has a higher transfer rate and greater cell endurance than MLC NAND flash memory. MLC NAND, on the other hand, benefits from lower price and higher capacity. In order to achieve higher performance than traditional SSDs, an interleaving technique that places NAND flash chips in parallel is essential. However, using the traditional FTL (flash translation layer) on an SSD with only MLC NAND chips is inefficient because the size of a logical block becomes large as the mapping address unit grows. In this paper, we proposed a HFTL (hybrid flash translation layer) which makes use of chained-blocks, combining SLC NAND and MLC NAND flash memories in parallel. Experimental results show that for most of the traces studied, the HFTL in an SSD configuration composed of 80% MLC NAND and 20% SLC NAND memories can improve performance compared to other solid state disk configurations, composed of either SLC NAND or MLC NAND flash memory alone.     

SMARC：一种结合SLC和MLC的混合固态盘架构

提出了一种新的内部混合架构的SSD（SMARC）, 它同时包含SLC和MLC闪存体, 而不是只有SLC或MLC。通过定期在两个不同部分（SLC和MLC区域）之间根据运行的工作负载动态迁移数据, 所提出的架构能够充分利用各自的优势互补, 以提高系统整体的性能、可靠性和能源消耗。关于各种工作负载的仿真结果显示出, SMARC可以有效地改善近一个数量级的性能, 同时, 显著地提高可靠性和减少能源消耗。而且, SMARC可以很容易地扩展以提供各种差异化的存储服务, 为现代存储系统提供重要的应用。     

集成硬件加密的加密固态盘的设计与实现

为了使NAND Flash固态盘的数据在存取过程中被透明加解密且提高整个安全存储系统的集成度,在分析固态盘体系结构的基础上,提出了在固态盘内部集成硬件加密功能的方法,并给出了加密固态盘的设计方案;利用FPGA设计实现了嵌入到固态盘内的硬件加密模块,并结合通用的ATA Flash盘控制器和NAND Flash芯片实现了完整的加密固态盘;实验结果表明,该加密固态盘实现了全盘数据加密,而且由于加密模块全硬件实现,加解密速度快且不占用系统资源,增加加密模块后不影响固态盘的性能。     

Sub-Join:面向闪存数据库的查询优化算法

固态硬盘具有高速的随机读取速度、低功耗、体积小等特点,被认为将取代磁盘成为新一代的数据存储设备。但是闪存数据库的查询性能的提高却远小于固态硬盘相比于磁盘I/O性能的提高,其原因在于现有的数据库是基于磁盘设计的,不能充分发挥固态硬盘的高速性能。提出一种名为子连接(Sub-Join)的连接算法。首先将数据表的连接列和主键投影为新的子表,然后对子表进行接连操作,最后根据子表的连接结果再从原始数据表中回取查询结果。通过和开源数据库Oracle Berkeley DB的比较实验,结果表明子连接算法比原有算法的性能提高了40%～100%,充分说明了它的优越性。     

一种基于闪存固态硬盘的辅助缓冲池设计

基于磁盘数据库系统的瓶颈主要在磁盘I／O,通常采用缓冲池的设计,将读到的数据页先放入到内存缓冲池后再进行操作。因此,缓存池的大小直接决定了数据库的性能。通过研究基于闪存固态硬盘的特性,提出了一种基于闪存固态硬盘的辅助缓冲池设计。最后,通过修改开源数据库MySQL InnoDB存储引擎,并通过TPC-C实验对比分析了启用辅助缓冲池后数据库的性能可有100％-320％的提高。     

Modeling the aging process of flash storage by leveraging semantic I/O

The major advantages of flash memory such as small physical size, no mechanical components, low power consumption, and high performance have made it likely to replace the magnetic disk drives in more and more systems. Many research efforts have been invested in employing flash memory to build high performance and large-scale storage systems for data-intensive applications. However, the endurance cycle of flash memory has become one of the most important challenges in further facilitating the flash memory based systems. This paper proposes to model the aging process of flash memory based storage systems constructed as a Redundant Array of Independent Disks (RAID) by leveraging the semantic I/O. The model attempts to strike a balance between the program/erase cycles and the rebuilding process of RAID. The analysis results demonstrate that a highly skewed data access pattern ages the flash memory based RAID with an arbitrary aging rate, and a properly chosen threshold of aging rate can prevent the system from aging with a uniform data access pattern. The analysis results in this paper provide useful insights for understanding and designing effective flash memory based storage systems.     

Efficient journaling writeback schemes for reliable and high-performance storage systems

We propose a efficient writeback scheme that enables guaranteeing throughput in high-performance storage systems. The proposed scheme, called de-fragmented writeback (DFW), reduces positioning time of storage devices in writing workloads, and thus enables fast writeback in storage systems. We consider both of storage media in designing DFW scheme; traditional rotating disk and emerging solid-state disks. First, sorting and filling holes methods are used for rotating disk media for the higher throughput. The scheme converts fragmented data blocks into sequential ones so that it reduces the number of write requests and unnecessary disk-head movements. Second, flash block aware clustering-based writeback scheme is used for solid-state disks considering the characteristics of flash memory. The experimental results show that our schemes guarantee system’s high throughput while guaranteeing data reliability.     

A high performance NAND array file system based on multiple NAND flash memories

The existing NAND flash memory file systems have not taken into account multiple NAND flash memories for large-capacity storage. In addition, since large-capacity NAND flash memory is much more expensive than the same capacity hard disk drive, it is cost wise infeasible to build large-capacity flash drives. To resolve these problems, this paper suggests a new file system called NAFS for large-capacity storage with multiple small-capacity and low-cost NAND flash memories. It adopts a new cache policy, mount scheme, and garbage collection scheme in order to improve read and write performance, to reduce the mount time, and to improve the wear-leveling effectiveness. Our performance results show that NAFS is more suitable for large-capacity storage than conventional NAND file systems such as YAFFS2 and JFFS2 and a disk-based file system for Linux such as HDD-RAID5-EXT3 in terms of the read and write transfer rate using a double cache policy and the mount time using metadata stored on a separate partition. We also demonstrate that the wear-leveling effectiveness of NAFS can be improved by our adaptive garbage collection scheme.     

ASA-FTL: An adaptive separation aware flash translation layer for solid state drives

The flash-memory based Solid State Drive (SSD) presents a promising storage solution for increasingly critical data-intensive applications due to its low latency (high throughput), high bandwidth, and low power consumption. Within an SSD, its Flash Translation Layer (FTL) is responsible for exposing the SSD’s flash memory storage to the computer system as a simple block device. The FTL design is one of the dominant factors determining an SSD’s lifespan and performance. To reduce the garbage collection overhead and deliver better performance, we propose a new, low-cost, adaptive separation-aware flash translation layer (ASA-FTL) that combines sampling, data clustering and selective caching of recency information to accurately identify and separate hot/cold data while incurring minimal overhead. We use sampling for light-weight identification of separation criteria, and our dedicated selective caching mechanism is designed to save the limited RAM resource in contemporary SSDs. Using simulations of ASA-FTL with both real-world and synthetic workloads, we have shown that our proposed approach reduces the garbage collection overhead by up to 28% and the overall response time by 15% compared to one of the most advanced existing FTLs. We find that the data clustering using a small sample size provides significant performance benefit while only incurring a very small computation and memory cost. In addition, our evaluation shows that ASA-FTL is able to adapt to the changes in the access pattern of workloads, which is a major advantage comparing to existing fixed data separation methods.     

Profit data caching and hybrid disk‐aware Completely Fair Queuing scheduling algorithms for hybrid disks

Recently, a hybrid disk drive that integrates a small amount of flash memory within a mechanical drive has received significant attention. The hybrid drive extends the storage hierarchy by using flash memory to cache data from the mechanical disk. Unfortunately, current caching architectures fail to fully exploit the potential of the hybrid drive. Furthermore, current disk input/output (I/O) schedulers are optimized for rotational mechanical disk drives and thus must be re‐targeted for the hybrid disk drive. In this paper, we propose a new data caching scheme, called Profit Caching, for hybrid drives. Profit Caching is a self‐optimizing caching algorithm. It considers and seamlessly integrates all possible data characteristics that impact the performance of hybrid drives, including read count, write count, sequentiality, randomness, and recency, to determine the caching policy. Moreover, we propose a hybrid disk‐aware Completely Fair Queuing (HA‐CFQ) scheduler to avoid unnecessary I/O anticipations of the CFQ scheduler. We have implemented Profit Caching and HA‐CFQ scheduler in the Linux kernel. Coupled with a trace‐driven simulator, we have also conducted detailed experiments under a variety of workloads. Experimental results show that Profit Caching provides significantly improved performance compared with the previous schemes. In particular, the throughput of Profit Caching outperforms previous Random Access First and FlashCache caching schemes by factors of up to 1.8 and 7.6, respectively. In addition, the HA‐CFQ scheduler reduces the total execution time of the CFQ scheduler by up to 1.74%. Finally, the experimental results show that the runtime overhead of Profit Caching is extremely insignificant and can be ignored. Copyright © 2014 John Wiley & Sons, Ltd.     

基于磁盘和固态硬盘的混合存储系统研究综述

大数据和云计算环境下海量增长的数据对存储系统的超高容量和体系结构带来了极大的挑战。目前存储系统的发展趋向于大容量、低成本和高性能,然而任何单一的存储器件如传统的机械磁盘（HDD）、固态硬盘（SSD）、非易失型性随机存储器等由于其固有的物理特性的限制,并不能满足以上的需求。将不同的存储介质混合组合成高效的存储系统是一个好的解决方法,固态硬盘作为一种高可靠性、低能耗、高性能的存储器被越来越广泛地运用到混合存储系统。通过将固态硬盘与传统磁盘进行组合,利用固态硬盘的高性能和传统磁盘低成本大容量的特点,能够为用户提供大容量的存储空间,保证系统的高性能,同时还能降低成本。通过阐述SSD与HDD混合存储系统的研究现状,对不同的SSD与HDD混合存储系统进行分类总结;然后针对缓存架构和设备同层架构这两种目前最流行的存储架构中涉及到的关键技术和不足进行讨论;最后对基于SSD和HDD的混合存储技术进行概括总结,并对今后该领域的研究重点和方向进行展望。