S-RAID 5:一种适用于顺序数据访问的节能磁盘阵列

磁盘及其冷却系统是现代存储系统中能耗的主体,已有的节能研究主要面向以随机数据访问为主的存储系统,对于广泛存在的以顺序数据访问为主的存储系统,如视频监控、虚拟磁带库(VTL)、连续数据保护(CDP)等,针对该类系统固有访问模式的节能研究较少.为此,提出了适用于顺序数据访问的节能磁盘阵列S-RAID 5,采用局部并行策略:阵列中的存储区被分成若干组,组内采用并行访问模式,分组有利于调度部分磁盘运行而其余磁盘待机,组内并行用以提供性能保证.在S-RAID5磁盘阵列中运行磁盘调度算法,辅以合适的Cache策略来过滤少量的随机访问,S-RAID5可获得显著的节能效果.在32路D1标准的视频监控模拟实验中,在满足性能需求、单盘容错的条件下,24小时功耗测量实验表明:S-RAID5的功耗为节能磁盘阵列Hibernator功耗的59％,eRAID功耗的23％,PARAID、GRAID功耗的21％左右.     

S-RAID中基于连续数据特征的写优化策略

节能型磁盘阵列S-RAID通过对磁盘分组,关闭部分磁盘,降低存储系统部分性能来实现节能.为避免启动已关闭磁盘而产生额外能耗,S-RAID中的写操作全部采用"读-改-写"方式,影响了S-RAID的写性能.本研究提出一种S-RAID的优化结构:LS-RAID,在不提高存储系统能耗的条件下,优化S-RAID的写性能.LS-RAID适用于以连续访问为主的应用,通过磁盘分区,分离存储系统中的随机访问和顺序访问,降低了随机访问对存储系统性能的影响;提出一种数据增量校验算法,避免了写过程中对数据盘旧数据的读操作,降低了因"读-改-写"导致的写惩罚.实验表明,与S-RAID相比,在不增加系统能耗的情况下,LS-RAID的写速率可以提升至少56%.在提供相同写性能的条件下,LS-RAID可以关闭更多磁盘,进一步降低了存储系统能耗,提升了节能效果.     

混合S-RAID:一种适于连续数据存储的节能数据布局

存储系统规模的日益增大,其高能耗成为一个无法忽视的问题,因此对存储系统的节能研究十分重要.提出一种由SSD固态盘与普通磁盘组成的混合S-RAID结构,通过关闭部分处于空闲状态的磁盘,达到节能效果.混合S-RAID将包括超级块在内的少量随机读写数据放在由SSD组成的RAID1中,将连续数据放在由普通磁盘组成的S-RAID中,S-RAID对磁盘分组,连续数据访问模式下只有一个组处于活动状态,关闭处于空闲状态的磁盘组.在仅增加少量成本的前提下,提高了存储系统的节能效果.混合S-RAID适用于各种以连续数据访问为主要特征的应用环境.实验表明,由12块普通磁盘和两块SSD固态盘组成的混合S-RAID 5与同级别RAID 5相比,能耗仅为RAID 5的28％.     

基于对象存储的负载均衡存储策略

对象存储文件系统中将大数据文件分片存储到多个存储节点上,以获取更好的并行I/O性能,提高系统吞吐率.现有对象存储文件系统的存储策略并未充分考虑存储对象本身负载的动态变化,不利于提高系统资源利用率.针对此问题,考虑存储对象的空间及I/O等负载实时变化,提出了一种简单、灵活、高效的负载均衡存储策略,并对该策略进行了实现.实验结果表明,该策略能有效提高对象存储系统资源的利用率和吞吐率,保证对象存储文件系统高效的读写性能.     

Swift云存储环境下基于I/O负载均衡的读取策略

Swift是开源云计算平台OpenStack中云存储服务组件,为平台提供廉价、可靠、安全的云存储服务.针对Swift没有充分利用存储系统的备份数据来实现并行读取操作及负载均衡的这一问题,提出了基于I/O负载均衡的并发读策略.实验结果表明,该策略不仅能够充分利用备份数据来达到存储设备读操作的负载均衡,而且能够实现数据的并行读取,提高平台整体读性能.     

海量存储系统的发展与展望

从存储网络技术、系统架构、数据保护、绿色存储等方面综合分析了海量存储系统的发展趋势,并对新一代海量存储-并行海量存储系统的相关理论和关键技术做了分析。并行海量存储系统应具有自动负载均衡、高可用、支持重复数据删除、自动分层存储、绿色节能等先进特性。     

基于动态布局的块级网络存储系统VISA

高性能、可扩展的网络存储系统在当今数据密集型应用中日益重要.分布式RAID作为一种存储体系结构,被广泛应用在集群和分布式计算环境中,但其机械的数据放置策略会导致在数据一致性维护中读写性能的下降.基于分布式RAID和存储虚拟化的理念,提出了一种新型块级网络存储系统VISA(virtual interface storage architecture).VISA系统不仅可以实现本地和远程的快速存储访问,而且可以根据当前各存储节点的负载状况和数据布局策略,将用户I/O请求的逻辑块地址动态映射到物理块地址,从而达到负载均衡与高性能的统一.测试结果显示,使用这种动态映射策略的VISA系统与传统的采用分布式RAID结构的IP-SAN相比,顺序写性能提高了78.66%～141.77%,顺序读性能提高了34.89%～51.73%.     

云存储多卷负载均衡的LSM键值存储系统

单个云存储卷的IOPS和带宽性能受到限制，通过组合使用多个云存储卷的方式能以较低的费用获得更高的性能.但是，现有工作缺乏针对多云存储卷优化的LSM键值存储系统的探究.首先将现有多路径或哈希负载均衡的方案应用于使用多云存储卷的LSM键值存储系统，相对单个大容量卷的性能有显著提升；但是，现有多卷负载均衡方案的写数据策略，无法感知LSM键值存储系统的数据布局特点，导致各成员卷之间仍然存在负载不均衡的问题，不能充分发挥出多卷的最大性能.为此，提出一种云存储多卷负载均衡的LSM键值存储系统TANGO.在LSM键值存储系统由compaction新生成的sstable落盘之前，先根据统计的各个成员卷的关键信息，判断sstable与各成员卷的键范围重叠情况，然后选择键范围重叠最小的成员卷进行写入；针对读为主的负载，无法通过compaction达到负载均衡，TANGO采用后台数据迁移方式进一步达到负载均衡.在亚马逊云存储卷上的评估表明，相比相同存储容量的单卷，采用了TANGO方案的同等容量的多卷可提高7倍左右的性能；相比其它多卷方案，TANGO能提升20%以上的性能，且各成员卷间负载更加均衡.     

基于前验负载差异的负载平衡性能模型

基于有限差分离散的并行应用非常普遍,针对此类问题的负载平衡性能评估,引入了一个刻画应用问题负载平衡能力的关键参数:最大负载变化率,推导了一个以并行效率为目标函数的负载平衡性能模型,涉及问题规模、并行通信计算比、离散格式复杂度和并行规模等.以POP全球海洋模式并行程序为测试实例,验证了该模型的性能.结果显示最大负载变化率作为衡量负载平衡程度的指标是有效的,基于模型的预测性能与实测性能在总体趋势上基本吻合.该性能模型对基于有限元、有限体积等其他局部离散格式的大型并行计算应用的负载平衡能力评估也具有参考价值.     

基于HBase的交通流数据实时存储系统

交通流数据具有多来源、高速率、体量大等特征,传统数据存储方法和系统暴露出扩展性弱和存储实时性低等问题.针对上述问题,设计并实现了一套基于HBase交通流数据实时存储系统.该系统采用分布式存储架构,通过前端的预处理操作对数据进行规范化整理,利用多源缓冲区结构对不同类型的流数据进行队列划分,并结合一致性哈希算法、多线程技术、行键优化设计等策略将数据并行存储到HBase集群服务器中.实验结果表明:该系统与基于Oracle的实时存储系统相比,其存储性能提升了3~5倍;与原生的HBase方法相比,其存储性能提升了2~3倍,并且具有良好的扩展性能.     

An energy-efficient storage for video surveillance

With the rapid growth of the video surveillance applications, the storage energy consumption of video surveillance is more noticeable, but existed energy-saving methods for massive storage system most concentrate on the data centers mainly with random accesses. The storage of video surveillance has inherent access pattern, and requires special energy-saving approach to save more energy. An energy-efficient data layout for video surveillance, Semi-RAID is proposed. It adopts partial-parallelism strategy, which partitions disk data into different groups, and implements parallel accesses in each group. Grouping benefits to realize only partial disks working and the rest ones idle, and inner-group parallelism provides the performance guarantee. In addition, greedy strategy for address allocation is adopted to effectively prolong the idle period of the disks; particular Cache strategies are used to filter the small amount of random accesses. The energy-saving efficiency of Semi-RAID is verified by a simulated video surveillance consisting of 32 cameras with D1 resolution. The experiment shows: Semi-RAID can save 45 % energy than Hibernator; 80 % energy than PARAID; 33 % energy than MAID; 79 % energy than eRAID-5, while providing single disk fault tolerance and meeting the performance requirement, such as throughput.     

ADL-RAID: Energy-Saving Data Layout for Dynamic Loads

With the rapid development of information technology and the explosive growth of data, the scale of storage equipment is growing rapidly. The high energy consumption storage devices have become a serious problem for data centers. For data storage, the model of sequential data access a storage system is commonly used. Aiming at the characteristics of a sequential data storage system, this paper, we propose a structure, named Adapted to Dynamic Load based on Redundant Array Independent Disks (ADL-RAID) which is an effective energy-saving data layout for dynamic loads based on the existing Semi-Redundant Array Independent Disks (S-RAID). ADL-RAID inherits the local parallel energy-saving strategy, uses an address mapping mechanism, and allocates storage space to satisfy the performance requirements for the user requested application. By sensing different loads, ADL-RAID allocates storage space for its dynamic loads with the appropriate parallelism. One or several data disks are used when the load is minimized, and all the data disks are used in parallel when the load is maximized. Experimental results show that, for 100% continuous write request, ADL-RAID saves 33.6% energy consumption than S-RAID5 and improves write performance than S-RAID5 by 34.3%. Thus, ADL-RAID has higher availability and is ideal for sequential data storage applications.     

Exploiting flash memory characteristics to improve performance of RAIS storage systems

Redundant array of independent SSDs (RAIS) is generally based on the traditional RAID design and implementation. The random small write problem is a serious challenge of RAIS. Random small writes in parity-based RAIS systems generate significantly more pre-reads and writes which can degrade RAIS performance and shorten SSD lifetime. In order to overcome the well-known write-penalty problem in the parity-based RAID5 storage systems, several logging techniques such as Parity Logging and Data Logging have been put forward. However, these techniques are originally based on mechanical characteristics of the HDDs, which ignore the properties of the flash memory. In this article, we firstly propose RAISL, a flash-aware logging method that improves the small write performance of RAIS storage systems. RAISL writes new data instead of new data and pre-read data to the log SSD by making full use of the invalid pages on the SSD of RAIS. RAISL does not need to perform the pre-read operations so that the original characteristics of workloads are kept. Secondly, we propose AGCRL on the basis of RAISL to further boost performance. AGCRL combines RAISL with access characteristic to guide read and write cost regulation to improve the performance of RAIS storage systems. Our experiments demonstrate that the RAISL significantly improves write performance and AGCRL improves both of write performance and read performance. AGCRL on average outperforms RAIS5 and RAISL by 39.15% and 16.59% respectively.     

A high-performance and endurable SSD cache for parity-based RAID

Solid-state drives (SSDs) have been widely used as caching tier for disk-based RAID systems to speed up dataintensive applications. However, traditional cache schemes fail to effectively boost the parity-based RAID storage systems (e.g., RAID-5/6), which have poor random write performance due to the small-write problem. What’s worse, intensive cache writes can wear out the SSD quickly, which causes performance degradation and cost increment. In this article, we present the design and implementation of KDD, an efficient SSD-based caching system which Keeps Data and Deltas in SSD. When write requests hit in the cache, KDD dispatches the data to the RAID storage without updating the parity blocks to mitigate the small write penalty, and compactly stores the compressed deltas in SSD to reduce the cache write traffic while guaranteeing reliability in case of disk failures. In addition, KDD organizes the metadata partition on SSD as a circular log to make the cache persistent with low overhead.We evaluate the performance of KDD via both simulations and prototype implementations. Experimental results show that KDD effectively reduces the small write penalty while extending the lifetime of the SSD-based cache by up to 6.85 times.     

A reliable and energy-efficient storage system with erasure coding cache

In modern energy-saving replication storage systems, a primary group of disks is always powered up to serve incoming requests while other disks are often spun down to save energy during slack periods. However, since new writes cannot be immediately synchronized into all disks, system reliability is degraded. In this paper, we develop a high-reliability and energy-efficient replication storage system, named RERAID, based on RAID10. RERAID employs part of the free space in the primary disk group and uses erasure coding to construct a code cache at the front end to absorb new writes. Since code cache supports failure recovery of two or more disks by using erasure coding, RERAID guarantees a reliability comparable with that of the RAID10 storage system. In addition, we develop an algorithm, called erasure coding write (ECW), to buffer many small random writes into a few large writes, which are then written to the code cache in a parallel fashion sequentially to improve the write performance. Experimental results show that RERAID significantly improves write performance and saves more energy than existing solutions.     

支持高并发访问的新型NVM存储系统

I/O系统软件栈是影响NVM存储系统性能的重要因素。针对NVM存储系统的读写速度不均衡、写寿命有限等问题，设计了同异步融合的访问请求管理策略；在使用异步策略管理数据量较大的写操作的同时，仍然使用同步策略管理读请求和少量数据的写请求。针对多核处理器环境下不同计算核心访问存储系统时地址转换开销大的问题，设计了面向多核处理器地址转换缓存策略，减少地址转换的时间开销。最后实现了支持高并发访问NVM存储系统（CNVMS）的原型，并使用通用测试工具进行了随机读写、顺序读写、混合读写和实际应用负载的测试。实验结果表明，与PMBD相比，所提策略能提高1%~22%的读写速度和9%~15%的IOPS，验证了CNVMS策略能有效提高NVM存储系统的I/O性能和访问请求处理速度。     

一种新型瓦记录磁盘的高可靠数据存储方法

近年来,传统磁记录的存储密度增长已经达到极限,为了满足快速增长的数据容量需求,多种新型存储技术不断涌现,其中瓦记录（shingled magnetic recording,SMR）技术已实现商业化,在企业实际应用.由于瓦记录磁盘的叠瓦式结构,磁盘在随机写入时会引起写放大,造成磁盘性能下降.这一问题在部署传统的高可靠存储方案（如RAID5）时会变得更加严重,原因在于校验数据更新频率很高,磁盘内出现大量的随机写请求.研究发现瓦记录内部其实存在具有原位更新能力的“可覆盖写磁道（free track）”,基于“可覆盖写磁道”,提出了一种专门针对瓦记录盘的高可靠数据存储方法——FT-RAID,以替代经典的RAID5方法,实现一种廉价、大容量、高可靠的存储系统.FT-RAID包含两个部分：“可覆盖写磁道映射（FT-mapping）”和“可覆盖写磁道缓冲区（FT-buffer）”.FT-mapping实现了一种瓦记录友好的RAID映射方式,将频繁更新的校验块数据映射至“可覆盖写磁道”;FT-buffer实现了一种瓦记录友好的两层缓冲区结构,上层确保了热数据能够原位更新,下层提高了缓冲区的容量.基于真实企业I/O访问记录的实验结果表明,与传统RAID 5相比,FT-RAID能够减少80.4%的写放大率,显著提高存储系统整体性能.     

Reconstruct versus read-modify writes in RAID

RAID5 (Redundant Arrays of Independent Disk level 5) is a popular paradigm, which uses parity to protect against single disk failures. A major shortcoming of RAID5 is the small write penalty, i.e., the cost of updating parity when a data block is modified. Read-modify writes and reconstruct writes are alternative methods for updating small data and parity blocks. We use a queuing formulation to determine conditions under which one method outperforms the other. Our analysis shows that in the case of RAID6 and more generally disk arrays with k check disks tolerating k disk failures, RCW outperforms RMW for higher values of N and G. We note that clustered RAID and variable scope of parity protection methods favor reconstruct writes. A dynamic scheme to determine the more desirable policy based on the availability of appropriate cached blocks is proposed.     

RAID5 performance with distributed sparing

Distributed sparing is a method to improve the performance of RAID5 disk arrays with respect to a dedicated sparing system with N+2 disks (including the spare disk), since it utilizes the bandwidth of all N+2 disks. We analyze the performance of RAID5 with distributed sparing in normal mode, degraded mode, and rebuild mode in an OLTP environment, which implies small reads and writes. The analysis in normal mode uses an M/G/1 queuing model, which takes into account the components of disk service time. In degraded mode, a low-cost approximate method is developed to estimate the mean response time of fork-join requests resulting from accesses to recreate lost data on the failed disk. Rebuild mode performance is analyzed by considering an M/G/1 vacationing server model with multiple vacations of different types to take into account differences in processing requirements for reading the first and subsequent tracks. An iterative solution method is used to estimate the mean response time of disk requests, as well as the time to read each disk, which is shown to be quite accurate through validation against simulation results. We next compare RAID5 performance in a system (1) without a cache; (2) with a cache; and (3) with a nonvolatile storage (NVS) cache. The last configuration, in addition to improved read response time due to cache hits, provides a fast-write capability, such that dirty blocks can be destaged asynchronously and at a lower priority than read requests, resulting in an improvement in read response time. The small write penalty is also reduced due to the possibility of repeated writes to dirty blocks in the cache and by taking advantage of disk geometry to efficiently destage multiple blocks at a time     

A Case for Continuous Data Protection at Block Level in Disk Array Storages

This paper presents a study of data storages for continuous data protection (CDP). After analyzing the existing data protection technologies, we propose a new disk array architecture that provides Timely Recovery to Any Point-in-time, referred to as TRAP. TRAP stores not only the data stripe upon a write to the array but also the time-stamped Exclusive ors (xors) of successive writes to each data block. By leveraging the xor operations that are performed upon each block write in today's RAID4/5 controllers, TRAP does not incur noticeable performance overhead. More importantly, TRAP is able to recover data very quickly to any point-in-time upon data damage by tracing back the sequence and history of xors resulting from writes. What is interesting is that the TRAP architecture is very space efficient. We have implemented a prototype of the new TRAP architecture using software at the block level and carried out extensive performance measurements using TPC-C benchmarks running on Oracle and Postgres databases, TPC-W running on a MySQL database, and file system benchmarks running on Linux and Windows systems. Our experiments demonstrated that TRAP not only is able to recover data to any point-in-time very quickly upon a failure but also uses less storage space than traditional daily incremental backup/snapshot. Compared to the state-of-the-art CDP technologies, TRAP saves disk storage space by one to two orders of magnitude with a simple and a fast encoding algorithm. In addition, TRAP can provide two-way data recovery with the availability of only one reference image in contrast to the one-way recovery of snapshot and incremental backup technologies.