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Emergence of Solid-State Drives (SSDs) have evolved the data storage industry where they are rapidly replacing Hard Disk Drives (HDDs) due to their superiority in performance and power. Meanwhile, SSDs have reliability issues due to bit errors, bad blocks, and bad chips. To help reliability, Redundant Array of Independent Disks (RAID) configurations, originally proposed to increase both performance and reliability of HDDs, are also applied to SSD arrays. However, the conventional reliability models of HDD RAID cannot be intactly applied to SSD arrays, as the nature of failures in SSDs are totally different from HDDs. Previous studies on the reliability of SSD arrays are based on the deprecated SSD failure data, and only focus on limited failure types, device failures, and page failures caused by the bit errors, while recent field studies have reported other failure types including bad blocks and bad chips, and a high correlation between failures. In this paper, we investigate the reliability of SSD arrays using field storage traces and real-system implementation of conventional and emerging erasure codes. The reliability is evaluated by statistical fault injection experiments that post-process the usage logs obtained from the real-system implementation, while the fault/failure attributes are obtained from the state-of-the-art field data by previous works. As a case study, we examine conventional RAID5 and RAID6 and emerging Partial-MDS (PMDS) codes, Sector-Disk (SD) codes, and STAIR codes in terms of both reliability and performance using an open-source software RAID controller, MD (in Linux kernel version 3.10.0-327), and arrays of Samsung 850 Pro SSDs. Our detailed analysis on the data loss breakdown shows that a) emerging erasure codes fail to replace RAID6 in terms of reliability, b) row-wise erasure codes are the most efficient choices for contemporary SSD devices, and c) previous models overestimate the SSD array reliability by up to six orders of magnitude, as they just focus on the coincidence of bad pages (bit errors) and bad chips within a data stripe that holds the minority of root cause of data loss in SSD arrays. Our experiments show that the combination of bad chips with bad blocks is recognized as the major source of data loss in RAID5 and emerging codes (contributing more than 54 and 90 percent of data loss in RAID5 and emerging codes, respectively), while RAID6 remains robust under these failure combinations. Finally, the fault injection results reveal that SSD array reliability, as well as the failure breakdown is significantly correlated with SSD type.

In this work, the information theory and coding review was done as well as analysis of the modern error correction codes data storage application. Distributed data storage implementation based on error correction codes was done. Advantages of Reed-Solomon's extended codes in practical implementations in coding systems are using adjustment with byte structure of computer data. Possible use of Reed-Solomon codes in cascade codes as external cascade codes is described. The possibility of using Reed-Solomon codes for data storing in distributed systems is described. The principles of solving the problem of checksum values calculation are given in such a way that in case of loss of any given storage devices number, it would be possible to recover data from devices that continue working. The basic algorithms for solving this problem are considered, the algorithm of coding and algorithm of system recovery after loss of storage devices is described. The methods of parity checking for the case of one checksum device and the Reed-Solomon encoding method for RAID systems for the number of checksum devices greater than one are described. There are also two main implementations of Reed-Solomon encoding in RAID systems: the RAID controller and the distributed control point system, the specifics of their implementation, the principles of choosing a specific implementation depending on external conditions and system requirements.

Solid-state drives (SSDs) have been widely deployed in many platforms including consumer electronics, desktops and enterprise data centers due to their high performance and low power consumption. However, SSDs suffer from bit errors, and the bit error rate is time dependent since it increases as an SSD wears down. Traditional storage systems mainly use parity-based RAID to provide reliability guarantees by striping redundancy across multiple devices, but the effectiveness of traditional RAID schemes in SSDs remains debatable. Existing solutions are based on the block device SSDs, which used as faster HDD. But the characteristics of NAND flash memory and HDD are very different, Non-write-in place and background Garbage-collection have a negative impact on the real-time performance and reliability of the system. And almost all of the existing solutions are built on Black-Box SSD, which we cannot know the internal detail and data layout. As a result, they cannot take full advantage of flash memory features, reduce the parity updates costs and improve the system reliability. In this work, we proposed a new RAID system built on White-Box SSD, we call it WB-RAIS. For White-Box SSD, the FTL implement on the host side and it could be co-designed with the RAID controller. We exploit the characteristics of flash memory and build the strip mapping based on the physical block address. We also proposed a partial strip mechanism and smooth equipment replacement method. Experimental results show that WB-RAIS improves the write performance by an average of 20% and reduces the flash erase count 17–52% compared to Black-Box SSD RAID, and enhances the system reliability significantly.

Flash memory-based SSD-RAIDs are swiftly replacing conventional hard disk drives by exhibiting improved performance and stability, especially in I/O-intensive environments. However, the variations in latency and throughput occurring due to uncoordinated internal garbage collection cripples further boosting of performance. In addition, the unwanted variations in each SSD can influence the overall performance of the entire flash storage adversely. This performance bottleneck can be essentially reduced by an internal write cache in the RAID controller designed prudently by considering the crucial device characteristics. The state-of-the-art cache write for the RAID controller fails to incorporate device characteristics of flash memory-based SSDs and mitigates the performance gain. In this paper, we propose a novel cache design namely Layout-Aware Write Cache (LAWC) to overcome the performance barrier inculcated by independent garbage collections. LAWC implements (i) improved I/O scheduling for logically partitioned write caches, (ii) a destage write synchronization mechanism to allow individual write caches to flush write blocks into the SSD array in a coordinated manner, and (iii) a two-level hybrid cache algorithm utilizing small front level cache for the improved write cache efficiency. LAWC shows significant reduction in response time by 82.39 percent on RAID-0 and 68.51 percent on RAID-5 types of SSDs when compared with state-of-the-art write cache algorithms.

Redundant array of independent disk (RAID) offers a good option to provide device-level fault tolerance for solid-state drives (SSDs). However, parity update with either read–modify–write or read–reconstruct–write may introduce a lot of extra I/Os and thus significantly degrades SSD RAID performance. To reduce the parity update cost, elastic striping chooses to reconstruct new stripes with only the newly updated data chunks instead of directly updating parity chunks. However, it necessitates an RAID-level garbage collection (GC) process, which may incur a very high cost due to the mixture of hot and cold data chunks. To address this problem, we follow the idea of elastic striping and propose a workload-aware scheme (WAS) to reduce the RAID-level GC cost so as to improve the performance and endurance of SSD RAID. In particular, we first develop a novel lightweight hot data identification scheme which requires only a very small computation time and memory cost, then propose a hotness-aware elastic striping approach to separately write data chunks with different hotness to different regions in SSD RAID. To evaluate the effectiveness and efficiency of our WAS, we implement a prototype system on RAID-5 and RAID-6 arrays composed of commercial SSDs. Experimental results show that compared to original elastic striping, our scheme reduces 30.0%–70.6% (and 23.9%–63.2%) of chunk writes under the RAID-5 (and RAID-6) settings, and also reduces the average response time by 60.9%–79.3% (and 56.8%–80.9%) for RAID-5 (and RAID-6), respectively. Besides, our scheme also improves the endurance and reliability of SSD RAID compared to original elastic striping.

In a parity-based SSD RAID, small write requests not only accelerate the wear-out of SSDs due to extra writes for updating parities but also deteriorate performance due to associated expensive garbage collection. To mitigate the problem of small writes, a buffer is often added at the RAID controller to absorb overwrites and writes performed to the same stripe. However, this approach achieves only suboptimal efficiency because file layout information is invisible at the block level.This paper proposes RAFS, a RAID-aware file system, which utilizes a RAID-friendly data layout to improve the reliability and performance of SSD-based RAID 5. By leveraging delayed allocation of modern file systems, RAFS employs a stripe-aware buffer policy to coalesce writes to the same file. To reduce parity updates, RAFS compacts buffered updates and flushes back in stripe units to mitigate the parity update overhead. RAFS adopts a stripe-granularity allocation scheme to align writes to stripe boundaries. Experimental results show that RAFS can improve throughput by up to 90%, compared to Ext4.

We propose an alternative Redundant array of independent disks (RAID) data layout, Asymmetrical grouping data organization (AGDO), for object-based data de-duplication backup system. Object-based data deduplication is an effective solution for detecting duplicate data for compound files. We designed an asymmetrical grouping strategy, the disk in the array are partitioned into different groups, and in each group parallelism data access scheme is adopted, different types of objects are stored in different groups with maybe different group size, it can set and manage dynamic group size by using dynamic disk group adjustment algorithms. The performance of AGDO is evaluated and proved to be sufficient for the continuous storage application. The result is that disk accesses are concentrated in a part of the disks over a long time period and reduces the power consumption to 25% in a 10 disk configuration. Moreover, object-based de-duplication combined with AGDO has great potential in increasing data restoration speed for compound files. We have shown that this combination makes average restoration speed improved 11%.

With the explosive growth in data volume, the I/O bottleneck has become an increasingly daunting challenge for big data analytics. Economic forces, driven by the desire to introduce flash-based Solid-State Drives (SSDs) into the high-end storage market, have resulted in hybrid storage systems in the cloud. However, a single flash-based SSD cannot satisfy the performance, reliability, and capacity requirements of enterprise or HPC storage systems in the cloud. While an array of SSDs organized in a RAID structure, such as RAID5, provides the potential for high storage capacity and bandwidth, reliability and performance problems will likely result from the parity update operations. In this article, we propose a Log Disk Mirroring scheme (LDM) to improve the performance and reliability of SSD-based disk arrays. LDM is a hybrid disk array architecture that consists of several SSDs and two hard disk drives (HDDs). In an LDM array, the two HDDs are mirrored as a write buffer that temporally absorbs the small write requests. The small and random write data are written on the mirroring buffer by using the logging technique that sequentially appends new data. The small write data are merged and destaged to the SSD-based disk array during the system idle periods. Our prototype implementation of the LDM array and the performance evaluations show that the LDM array significantly outperforms the pure SSD-based disk arrays by a factor of 20.4 on average, and outperforms HPDA by a factor of 5.0 on average. The reliability analysis shows that the MTTDL of the LDM array is 2.7 times and 1.7 times better than that of pure SSD-based disk arrays and HPDA disk arrays.

In this paper, we propose Elastic-RAID, a new RAID architecture to achieve high performance and high reliability for large-scale distributed and parallel storage systems. The key idea behind Elastic-RAID is to smartly utilize the free space existing in parity-based disk arrays to store additional mirroring data. This additional mirroring data redundancy, when strategically and judiciously activated and exploited in a RAID system, enables improved system I/O performance, fault tolerance and recovery. Depending on the amount of free space available and whether the emphasis is on performance or reliability, the elasticity in Elastic-RAID is manifested in how each design objective is achieved. For the performance objective, Elastic-RAID improves small-write performance by writing original and mirroring data synchronously and leaving the costly parity update in the background at a later idle/lightly-loaded time. For the reliability objective, at least two concurrent disk failures can be tolerated when Elastic-RAID is employed in a RAID5 system that has 50 percent or more free space. Higher reliability is provided for important data when free space is less than 50 percent. To achieve the design goal of elasticity, we introduce a novel data layout and addressing scheme. Our extensive trace-driven evaluations on an Elastic-RAID prototype in the typical configurations of RAID5 show that Elastic-RAID boosts the small-write performance in the normal operational state by at least 40 percent, improves the user I/O performance in the reconstruction state by at least 30 percent and shortens the recovery time by at least 40 percent.

RAIDs (Redundant Array of Independent Disks) are widely used in storage systems to prevent data loss in case of hardware defects on a hard disk and to improve I/O performance. In case the RAID controller fails or in the context of a forensic investigation, the content of the RAID has to be reconstructed from the single disks or rather from disk images. Due to the variety of RAID controllers and various implementation and configuration possibilities, different parameters that are necessary for reconstruction are often unknown. This might be the case because the original configuration just has not been documented or in the forensic case, the administrator might not be cooperating and not willing to reveal the configuration. Using the original RAID system in such cases is not an option, too, because the original evidence should not be altered. We present a novel approach to automatically detect all parameters to reassemble the logical RAID volume based on block level entropy measurement and generic heuristics. We also provide a performance-optimized open source implementation of our approach that is also able to afterwards reassemble the entire logical RAID volume and to further recover single missing disks using the redundancy information as present in RAID-5.

This paper presents two mechanisms that can significantly improve the I/O performance of both hard and solid-state drives for read operations: KDSim and REDCAP. KDSim is an in-kernel disk simulator that provides a framework for simultaneously simulating the performance obtained by different I/O system mechanisms and algorithms, and for dynamically turning them on and off, or selecting between different options or policies, to improve the overall system performance. REDCAP is a RAM-based disk cache that effectively enlarges the built-in cache present in disk drives. By using KDSim, this cache is dynamically activated/deactivated according to the throughput achieved. Results show that, by using KDSim and REDCAP together, a system can improve its I/O performance up to 88% for workloads with some spatial locality on both hard and solid-state drives, while it achieves the same performance as a ‘regular system’ for workloads with random or sequential access patterns.

Solid State Drive (SSD) for the consumer market may not require extreme high performance, but it does want high density at a low cost. Redundant Array of Inexpensive (or Independent) Disks (RAID) are built up by a group of independent disk drives, not inside a disk drive. This makes a RAID system not as inexpensive as expected in the beginning and in the end the system often becomes expensive, large in size and complexity. It is not well suited for consumer applications. This paper proposes a new structure, to build up a high density SSD in a RAID system by using SD or MMC/ eMMC modules instead of independent drives. A SSD controller chip with embedded RAID (eRAID) multiple level functions was designed and applied to verify this proposal. By using this controller and eMMC modules, a redundant array of independent modules (RAIM) is built up as an inexpensive single drive and proven to work. The result revealed that a RAIM can be a single SSD drive as well as a micro-RAID system. By utilizing RAIM SSD units a more sophisticated RAID system can be constructed at lower costs and greater performance in a much smaller configuration, which is more suitable as home cloud storage, etc.

The need for huge storage archives rises with the ever growing creation of data. With today’s big data and data analytics applications, some of these huge archives become active in the sense that all stored data can be accessed at any time. Running and evolving these archives is a constant tradeoff between performance, capacity, and price. We present the LoneStar RAID, a disk-based storage architecture, which focuses on high reliability, low energy consumption, and cheap reads. It is designed for MAID systems with up to hundreds of disk drives per server and is optimized for “write once, read sometimes” workloads. We use dedicated data and parity disks, and export the data disks as individually accessible buckets. By intertwining disk groups into a two-dimensional RAID and improving single-disk reliability with intradisk redundancy, the system achieves an elastic fault tolerance that can at least recover all 3-disk failures. Furthermore, we integrate a cache to offload parity updates and a journal to track the RAID’s state. The LoneStar RAID scheme provides a mean time to data loss (MTTDL) that competes with today’s erasure codes and is optimized to require only a minimal set of running disk drives.

The current power managements in RAID array are mostly designed to conserve energy by spinning down partial disks of standard RAID architecture. However, spinning down several disks not only decreases disk parallelism, but also creates new problems, for example, partial chunks of the stripe cannot be accessed directly or multiple chunks of the same stripe are stored on the same disk, which affect spatial locality. We refer these problems as stripe degradation, which results in further performance degradation. To avoid such problems, this paper proposes a new RAID storage architecture called ThinRAID, which uses a subset of disks to build a capacity-adaptive RAID array based on the volume of the data set. Also, the other non-essential disks are spun down to save energy. When the workload is projected to become heavier based on our forecast model, data are migrated to disks that have recently transitioned from standby to active. Furthermore, we also propose a novel data reorganization algorithm that can minimize data migration. We have implemented ThinRAID in the Linux kernel and evaluated its performance and energy efficiency by replaying seven representative traces. Experimental results show that ThinRAID can save 15-27 percent on energy on average over conventional RAID, with minimum performance degradation. In comparison to PARAID, ThinRAID achieves up to 62 percent performance improvement.

One of the main goal of the operating system for the disk drives is to use the hardware efficiently. we can meet this goal using fast access time and large disk bandwidth that depends on the relative positions of the read-write head and the requested data. Since memory management allows multiprogramming so that operating system keeps several read/write request in the memory. In order to service these requests, hardware (disk drive and controller) must be used efficiently. To support this in disk drive, the hardware must be available to service the request. if the hardware is busy, we can’t service the request immediately and the new request will be placed in the queue of pending requests. Several disk scheduling algorithms are available to service the pending requests. among these disk scheduling algorithms, the algorithm that yields less number of head movement will remain has an efficient algorithm. In this research paper, we propose a new disk scheduling algorithm that will reduce the number of movement of head thereby reducing the seek time and it improves the disk bandwidth for modern storage devices. Our results and calculations show that, proposed disk scheduling algorithm will improve the performance of disk i/o by reducing average seek time compared to the existing disk scheduling algorithm. For few requests, the seek time and the total number of head movement is equal to SSTF or LOOK scheduling.

Solid-state drives (SSD) offer a significant performance improvement over the hard disk drives (HDD), however, it can exhibit a significant variance in latency and throughput due to internal garbage collection (GC) process on the SSD. When the SSDs are configured in a RAID, the performance variance of individual SSDs could significantly degrade the overall performance of the RAID of SSDs. The internal cache on the RAID controller can help mitigate the performance variability issues of SSDs in the array; however, the state-of-the-art cache algorithm of the RAID controller does not consider the characteristics of SSDs. In this paper, we examine the most recent write cache algorithm for the array of disks, and propose a synchronous independent write cache (SIW) algorithm. We also present a pre-parity-computation technique for the RAID of SSDs with parity computations, which calculates parities of blocks in advance before they are stored in the write cache. With this new technique, we propose a complete paradigm shift in the design of write cache. In our evaluation study, large write requests dominant workloads show up to about 50 and 20 percent improvements in average response times on RAID-0 and RAID-5 respectively as compared to the state-of-the-art write cache algorithm.

In this paper, a partial parity cache and data cache management method is presented for reducing the parity updating cost of a solid-state disk (SSD) based redundant array of inexpensive disk (RAID) system, thereby which the input/output (I/O) performance of the RAID system can be improved. SSDs have many advantages compared to hard disk drives. However, it is not advisable to directly add SSDs into a RAID system because doing so will decrease the performance and the life-time of the SSDs. In the RAID-5 system, parity generation includes read and write operations to the SSDs. Whenever there is a new write request to the RAID, the related parity must be updated and written to the SSDs. Such frequent parity updates result in poor RAID performance and shortens the life-time of the SSDs. This paper combines the prior methods and the proposed efficient buffer management method with a data cache. The proposed method reduces the number of read and write operations for generating parities in the RAID system. Experimental results show that the I/O performance of the RAID-5 system can be improved by 76% by using the proposed method.

this paper, a new approach of disk scheduling has been proposed to improve the throughput of modern storage device. After the invention of disk with movable head, researchers are making efforts continuously to improve the I/O performance by implementing many intelligent scheduling algorithms of disk accesses. Speeds of processor and memory capacity have been increased several times than the speed of the disk. Due to this difference in the speed of processor and the disk, I/O performance of disk has become an important bottleneck. Therefore, it is needed to develop some advanced methods for using disk more efficiently. Management of disk performance is an important aspect of operating system research and development. In this paper, a new disk scheduling algorithm has been developed and implemented to reduce the number of head movements. Experiment has been carried out to compare the performance of proposed algorithm with the performance of all six classical disk scheduling algorithms. Experiment shows that the numbers of head movements in existing classical disk scheduling algorithms such as FCFS, SSTF, SCAN, C-SCAN, LOOK and C-LOOK are high. But in proposed new optimized real-time disk scheduling algorithm, head movements are reduced and hence it maximizes the throughput for the modern storage devices. KeywordsSSTF, SCAN, C-SCAN, LOOK, C-LOOK, Scheduling

Although solid-state drives (SSDs) offer significant performance improvements over hard disk drives (HDDs) for a number of workloads, they can exhibit substantial variance in request latency and throughput as a result of garbage collection (GC). When GC conflicts with an I/O stream, the stream can make no forward progress until the GC cycle completes. GC cycles are scheduled by logic internal to the SSD based on several factors such as the pattern, frequency, and volume of write requests. When SSDs are used in a RAID with currently available technology, the lack of coordination of the SSD-local GC cycles amplifies this performance variance. We propose a global garbage collection (GGC) mechanism to improve response times and reduce performance variability for a RAID of SSDs. We include a high-level design of SSD-aware RAID controller and GGC-capable SSD devices and algorithms to coordinate the GGC cycles. We develop reactive and proactive GC coordination algorithms and evaluate their I/O performance and block erase counts for various workloads. Our simulations show that GC coordination by a reactive scheme improves average response time and reduces performance variability for a wide variety of enterprise workloads. For bursty, write-dominated workloads, response time was improved by 69 percent and performance variability was reduced by 71 percent. We show that a proactive GC coordination algorithm can further improve the I/O response times by up to 9 percent and the performance variability by up to 15 percent. We also observe that it could increase the lifetimes of SSDs with some workloads (e.g., Financial) by reducing the number of block erase counts by up to 79 percent relative to a reactive algorithm for write-dominant enterprise workloads.

In this paper, through the analysis of the redundant array of independent disks system (RAID), storage area network system (SAN), network storage system (NAS), based on RAID on the system FPGA is used to design a set of intelligent high speed disk storage protocol, through the test and analysis can meet the continuous data acquisition, the real-time data storage needs, in the software through providing high access speed increases memory buffer, large storage capacity and higher data security.

We propose Heterogeneous Disk Arrays (HDAs), which allow multiple RAID levels for database applications to coexist in a single disk array accommodating multiple RAID levels. Our main concern is to efficiently utilize disk bandwidth and capacity, while balancing disk loads in a cloud storage environment, however, a small number of disks is considered in this study for illustrative purposes. Individual RAID levels are adjusted to data availability requirements and workload demands. Adopting the most stringent availability requirements for all datasets would incur unnecessarily high bandwidth overhead for updating datasets, which do not have this requirement. Intermixing RAID levels is beneficial from the viewpoint of balancing disk loads, similarly to the striping paradigm in RAID5. The suitability of the RAID levels varies with database applications: RAID5 - reading/writing large datasets for data mining and warehousing, RAID1 -high performance OLTP applications. Several single pass data allocation methods are proposed in this paper and compared using synthetically generated allocation requests in associated papers.

The buffer cache plays an essential role in smoothing the gap between the upper level computational components and the lower level storage devices. A good buffer cache management scheme should be beneficial to not only the computational components, but also the storage components by reducing disk I/Os. Existing cache replacement algorithms are well optimized for disks in normal mode, but inefficient under faulty scenarios, such as a parity-based disk array with faulty disk(s). To address this issue, we propose a novel penalty-aware buffer cache replacement strategy, named Victim Disk(s) First (VDF) cache, to improve the reliability and performance of a storage system consisting of a buffer cache and disk arrays. VDF cache gives higher priority to cache the blocks on the faulty disks when the disk array fails, thus reducing the I/Os addressed directly to the faulty disks. To verify the effectiveness of the VDF cache, we have integrated VDF into the popular cache algorithms least frequently used (LFU) and least recently used (LRU), named VDF-LFU and VDF-LRU, respectively. We have conducted intensive simulations as well as a prototype implementation for disk arrays to tolerate one disk failure (RAID-5) and two disk failures (RAID-6). The simulation results have shown that VDF-LFU can reduce disk I/Os to surviving disks by up to 42.3 percent in RAID-5 and 50.7 percent in RAID-6, and VDF-LRU can reduce those by up to 36.2 percent in RAID-5 and 48.9 percent in RAID-6. Our measurement results also show that VDF-LFU can speed up the online recovery by up to 46.3 percent in RAID-5 and 47.2 percent in RAID-6 under spare-rebuilding mode, or improve the maximum system service rate by up to 47.7 percent in RAID-5 under degraded mode without a reconstruction workload. Similarly, VDF-LRU can speed up the online recovery by up to 34.6 percent in RAID-5 and 38.2 percent in RAID-6, or improve the system service rate by up to 28.4 percent in RAID-5.

RAID systems have been widely used by connecting several disks in parallel structure. to resolve the delay and bottleneck of data I/O. Recently, SSD based RAID systems are emerging since SSDs have better I/O performance than HDD. However, endurance and power consumption problems due to frequent write operation in SSD based RAID system should be resolved. In this paper, we propose a de-duplication method of parity disk in SSD based RAID system with expensive update cost. The proposed method segments chunk of parity data into small pieces and removes duplicate data, therefore, it can reduce wear-leveling and power consumption by decreasing write operation for duplicated parity data. Experimental results show that bit update rate of the proposed method is 16% in total disk, 31% in parity disk less than that of existing method in RAID-6 system using EVENODD erasure code, and the power consumption of the proposed method is 30% less than that of existing method. Besides the proposed method is 12% in total disk, 32% in parity disk less than that of existing method in RAID-5 system, and the power consumption of the proposed method is 36% less than that of existing method.

The Linux-based legacy server systems are configured and used with software RAID to improve the performance of the disk I/O. However, the problem is that the current Linux kernel and software RAID are difficult to optimize the high-performance block I/O because it is designed to be optimized for low-speed devices. Therefore, we propose the efficient method using recombination and re-mapping techniques to improve the performance of Block I/O Accelerator based software RAID level-0 provided on the Linux kernel level. This proposed method is designed to have more bandwidth at a time by reducing the number of system calls considering the block I/O characteristics of Linux kernel and RAID level 0. As a low-level I/O benchmarking tool, XDD is used to evaluate the performance of the proposed method. According to the experimental results, our performance gains are 15.24% on write bandwidth and 14.87% on read bandwidth compared with legacy software RAID 0.

Disk data density improvement will eventually be limited by the super-paramagnetic effect for perpendicular magnetic recording. Of the various new technologies being explored, Shingled Magnetic Recording (SMR) exposes as the most promising one to achieve high areal density and only make little changes to the manufacturing process. At present, high-capacity SMR drives are available from Seagate and HGST. Since SMR is leading next generation disk technology and increasing SMR drives will be used in storage systems, there is a great need to look over the current RAID storage techniques based on HDDs again. In this paper, we proposed a dynamic variable-width striping RAID (DVS-RAID) for SMR drives to reduce the parity updating cost. DVS-RAID never overwrites the old data, but always constructs a new full or partial stripe (variable-width stripe), and writes to the SMR drives through appending. In addition, taking the access characteristics of SMR drives into consideration, we present a new write cache management that exploits both spatial and temporal localities. The experiment with six real-world traces demonstrates that DVS- RAID exhibits a slightly lower performance than HDD- based RAID on update intensive workloads. However the performance of DVS-RAID is better than HDD-based RAID with sequential access, read-dominated workloads or workloads with rarely update.

This paper proposes a novel Delta redundant array of independent disks (RAID) technique that enhances small-write performance, resists disk failures of up to 75% in the RAID architecture. In order to generate parity data, three partial strips within a horizontal strip are used. To generate one parity element, Delta RAID requires access from two data disks, one parity disk. Delta RAID provides a fast recovery algorithm to correct various disk failures. Delta RAID also employs additional buffer caching replacement (BCR), which reduces the number of read, write operations by both merging small chunks into a larger chunk with buffer size, splitting a big chunk into many smaller chunks with buffer size. Compared to traditional GRID RAID(SPC, STAR), GRID RAID(SPC, EO),, GRID RAID(STAR, STAR), Delta RAID improves average small-write performance by 233%, 224%,, 176%, respectively, improves read performance by 289%, 268%,, 176%, respectively.

Existing conventional RAID storage systems are unable to provide expected storage performance under the explosive growth in data volumes. One of the solution is introducing SSDs (Solid State Drives), a promising storage medium which provides high performance and power efficiency, as a cache to loosen the performance bottleneck of RAID storage systems. However, using DRAM as a universe buffer area roughly, regardless of different characteristics between SSDs and the RAID, is inefficient. This paper proposes SHA (SSD aware Heterogeneous cache Algorithm), which divides the DRAM area into two regions: the SSD region and the RAID region, and adaptively adjusts these two regions according to the workload. The SSD region uses a victim-cost based replacement algorithm, and cached blocks are evaluated by their access patterns and the price of evicting them. The RAID region uses a LRU algorithm at the stripe granularity. This algorithm explores the parallelism of RAIDs and aggregates writes to reduce write penalties. Besides, a hot data filter is used to detect the temporal locality of evicted blocks from the RAID region, and blocks with temporal locality are sent to SSDs. This paper introduces the design of the SHA in detail, and performs intensively performance evaluations on the SHA.

NAND flash memory solid state devices are widely used in many platforms including consumer electronics and safety-critical embedded systems because they offer high performance and reliability. In previous work, we have developed a novel RAID architecture for NAND flash that protects a system from data loss in the case of failure, or wear-out, of individual flash chips. These mechanisms permit the recovery of data onto a new replacement chip when a particular element in the array reaches its endurance limit. However the use of this architecture in a hard real-time system is limited as the memory needs to be taken off-line while the replacement is actioned and so memory access times become non-deterministic with respect to time. In this paper we present a hot swapping technique for replacing elements in the array that are approaching their wear-out level that does not involve taking the array off-line — thereby increasing the systems availability and providing guaranteed response time. The result is that our hot-swapping architecture is more suited to applications with hard real-time constraints. We have implemented this technique in our FPGA-based SSD-aware RAID controller, complete with a metadata management framework to increase throughput and efficiency.

Different storage media have different performance in terms of fetching data. Most powerful one is RAM that has characteristics making it fast to serve I/O processes. Then, we have flash memory that has high performance of read tasks but less in write ones. Third one is HDD which is the slowest but most reliable in terms of preserving data. In this model, we used a combination of the first and third one to form a developed structure of RAID DP that has a much better performance. For parity disk drives, we used DRAM memory for its great performance. Because parity disks are the most overloaded with write processes. RAID 1 is also used as inner RAID system to preserve data stored in DRAM SSD (Solid State Drive) to HDD.

Traditional hierarchical RAID causes huge GPU overhead and does not support node failure. To resolve this problem, this paper proposes a new hierarchical redundant array of inexpensive disks (RAID)'s parity generation using pass-through GPU in multi virtual-machine (VM) environment. The proposed method reduces GPU overhead and parity generation time, and supports node failure compared to the traditional hierarchical RAID. Experimental results show that the average total encoding performance of the proposed method using multiple VMs is improved by 50.11% compared to Khasymski's RAID 51 with respect to various file sizes.

This chapter contains sections titled: Introduction Modeling Reliability of Energy-Efficient Parallel Disks Improving Reliability of MAID via Disk Swapping Experimental Results and Evaluation Related Work Conclusions References

In order to raise speed of reading data from disk array memory, scientific and technological personnel have introduced cache technology into disk array. Since this technique has been invented, although the efficiency of reading data have been solved, after writing operation of countless times in disk cache, data consistency problem has been prominent expression. Especially in this condition that false of electricity and machine abnormal failure, the consistency of the data is more difficult to guarantee. In this paper, we adopt Non-Volatile RAM (NVRAM) devices to realize that the data will not be lost in disk array cache after power failure. Here we design a kind of new cache organizational structure. We firstly introduce cache structure of two tables (real-time mapping table, backup mapping table) and a cache backup block. Then through these two tables, we can work to recover data through the copy between the two tables in the macroscopic, and in the microscopic through cache backup block can backup the cache data from writing failure. As power failure and system breakdown, we can ensure that data will not easily lose and the original data can recovery after system crash by this technology. Thus it ensures the consistency of the data cache.

This article presents the novel non-linear controller design method of rate actuated inverse dynamics. The rate actuated inverse dynamics controller design uses a novel variable structure control based anti-windup method to ensure that the actuator does not become overdriven when rate or deflection limits are reached. This allows the actuator to remain on both rate and deflection limits without the system becoming unstable. This is demonstrated in a non-linear simulation of a missile body rate autopilot using a multivariable controller designed using rate actuated inverse dynamics methods and, for comparison, a controller designed using robust inverse dynamics estimation. The simulation is performed with an advanced solver which uses a discontinuity detection mechanism to ensure that errors do not occur during the simulation due to the presence of multiple discontinuities. The results show that using a smaller actuator, with reduced rate limits, is not possible with the robust inverse dynamics estimation design. Conversely, the rate actuated inverse dynamics design demonstrates excellent performance, despite the actuator limiting in both deflection and rate of deflection. This illustrates the possibility of using smaller, less powerful actuators without sacrificing system stability.

With the growing technology, need for data storage systems is increasing day by day. Usage of inexpensive disk drives that provides higher disk capacity are less reliable. To increase the performance of the storage systems, multiple disk array are used so that different tasks can be executed concurrently. Different RAID levels have been implemented by researchers and are being used worldwide. All RAID levels requires a lot of storage space. If there is duplication in the data, then storing these duplicated data blocks is a wastage of storage space, as it is not required to store duplicated data blocks again and again. In this paper, we have proposed a new method i.e. dDRAID (data Deduplication over RAID Levels) by implementing the technique of deduplication over RAID levels so as to reduce the amount of storage space in order to provide better performance and reliability with maximum storage space available at least amount of cost involved. Implementation of deduplication over RAID levels in the proposed approach utilizes around 50% to 70% of storage space.

Reliable and high-performance network I/O mechanism is a critical part of exascale storage systems. In order to improve system reliability, some storage systems use replication and erasure coding. However, this is an additional cost and requires higher bandwidth. This paper proposes a novel method to implement a zero-overhead network RAID-5 with an active storage mechanism. The proposed method focuses on the write operation of the cluster-wide (network based) RAID system, and it can be generalized to the recovery process. In general, write throughput of the storage system with erasure coding is degraded because of the additional coding computation and the increased amount of transferred data. Our proposal solves this problem and enables us to implement a zero-overhead cluster-wide RAID system by avoiding client-side computation cost and network traffic. Furthermore, our proposed method enables the system to separate the traffic of the striped data blocks (source) and the parity generation traffic. Scalability of cluster-wide RAID can be highly increased with a dedicated network for the parity generation process. In addition, we propose an efficient implementation method that utilizes an InfiniBand remote direct memory access (RDMA) mechanism to minimize the number of memory copy operations. This implementation is built with zero-copy pipelines, and enables us to use a low-overhead inter-node data processing mechanism. The measured throughput gain was 32.6% compared to that of the naive method. The results show the same performance as RAID-0, which means that our proposed method achieves the zero-overhead cluster-wide RAID.

Inexpensive, reliable hard disk storage is increasingly required in both businesses and the home. As disk capacities increase and multiple drives are combined in one system the probability of multiple disk failures increases. Through the adoption of RAID 6 the capability to recover from up to two simultaneous disk failures becomes available. In this article, we present three different RAID 6 implementations each tailored to support different target applications and optimized to reduce overall hardware resource utilization. We present an optimal Reed-Solomon-based RAID 6 implementation for arrays of four disks. We also present the smallest in terms of hardware resource utilization as well having the highest throughput RAID 6 hardware solution for disk arrays of up to 15 drives. Finally, we present an implementation supporting up to 255 disks in a single array.

Recently, Solid state disk is mainly used because this device has lower power consumption as well as higher response time. But it features higher price and lower performance at delete and write operations compared with HDD. To compensate this defect, Hybrid hard disk with internal non-volatile flash memory was issued. This NVCache is used as a kind of cache for disk blocks. In this paper, an I/O scheme for H-HDD is proposed for improving low power consumption as well as response time. Our method is to use this NVCache as read cache mainly and write cache when write requests are concentrated. In read cache operation, disk blocks with higher priority determined on basis of time as well as spatial localities are prefetched, which can improve response time. The write operation is conducted only at write peak time as disk spindle up costs higher battery power as well as response time. Experiments results show that the suggested method can improve response time of H-HDD and lower the power consumption.

Write-through caching in modern disk drives enables the protection of data in the event of power failures as well as from certain disk errors when the write-back cache does not. Host system can achieve these benefits at the price of significant performance degradation, especially for small disk writes. We present new block-level techniques to address the performance problem of write-through caching disks. Our techniques are strongly motivated by some interesting results when the disk-level caching is turned off. By extending the conventional request merging, request bridging increases the request size and amortizes the inherent delays in the disk drive across more bytes of data. Like sector interleaving, request interleaving rearranges requests to prevent the disk head from missing the target sector position in close proximity, and thus reduces disk latency. We have evaluated our block-level approach using a variety of I/O workloads and shown that it increases disk I/O throughput by up to about 50%. For some real-world workloads, the disk performance is comparable or even superior to that of using the write-back disk cache. In practice, our simple yet effective solutions achieve better tradeoffs between data reliability and disk performance when applied to write-through caching disks.

In the ever-increasing development of network storage technology, distributed RAID has been a hot topic for data reliability and availability. To solve the problem of distributed RAID technology, such as: parallel access difficulty, long rebuild time, small write update and strip alignment problem, we design and implement file level distributed RAID system (BW-FILERAID) based on Blue Whale File System (BWFS). Also we do the research on resource allocation strategy, page cache management with parity data, consistence maintenance, online extension of RAID group, error detect and rebuild and small write optimization in BW-FILERAID. According to the testing results, the writing performance of BW-FILERAID is better than Linux soft RAID about 5%~50%, and the reading performance is equivalent to the RAID0. And it also has excellent extensibility.

In this work, we propose a novel hard disk technique, "AV Disk", for modern multimedia applications. Modern hard disk drives adopt complex sector layout mechanisms to reduce track and head switch overhead. While these complex sector layout mechanism can reduce average overhead involved in the track and head switch, they bring larger variability in the overhead. From a multimedia application's point of view, it is important to minimize the worst case I/O latency rather than to improve the average IO latency. We focus our effort to minimize track switch overhead as well as the variability in track switch overhead involved in disk I/O. We propose that track of the hard disk drive is aligned with a certain IO size. In this work, we develop an elaborate performance model with which we can compute the optimal IO unit size for multimedia applications. We propose that hard disk controller is responsible for positioning data blocks in the hard disk platter in such a manner that I/O units are not placed across the track boundaries, where a single I/O unit has size of 32---128 KByte. Optimal IO unit size is used in aligning the tracks in hard disk drives. We develop Skewed Sector Sparing technique in aligning a track with a given IO size. However, when the I/O unit for alignment is increased to 128 KByte, 17% of the disk space becomes unusable. Despite the decreased storage area, track aligning technique increases the overall performance of the hard disk. According to our simulation-based experiment, overall disk performance increases about 5---25%. Given that capacity of hard disk increases 100% every year, we cautiously regard it as reasonable tradeoff to increase the I/O latency of the disk.

Heterogeneous Disk Arrays (HDAs) allow resource sharing of their hardware by multiple RAID levels. RAID1 (mirrored disks) and RAID5 (distributed parity arrays) are the two RAID levels considered in this study. They are both single disk failure tolerant (1DFT), but differ significantly in their efficiency in processing database workloads. The goal of the study is to maximize the number of Virtual Array (VA) allocations in HDA. We develop an analysis to estimate the load per VA based on a few parameters: the fraction of accesses to small versus large blocks and the fraction of updates versus reads. A VA is allocated according to the RAID level, which minimizes the anticipated load based on input parameters. Operation in normal and degraded mode is considered for comparison purposes, but in fact allocations are carried out using the higher load in degraded mode to ensure that single disk failures will not result in overload. We report on parametric studies to gain insight into circumstances leading to a RAID1 or RAID5 classification. An allocation experiment with a synthetic workload is used to demonstrate the superiority of HDA with respect to purely RAID1 or RAID5 disk arrays. This analytic study can be extended to 2DFT arrays, namely RAID6 versus 3-way replication.

Redundant array of inexpensive disk (RAID)10 is known as the most reliable disk array architecture to tolerate up to half of total disk failures, but failure of two disks in the same mirror set still results in data loss. In this paper, we propose a new disk array architecture, mirroring and parity protected RAID (MP-RAID), which combines both mirroring and parity techniques to further improve reliability of disk arrays. The main idea behind MP-RAID is to protect the data by both mirroring and parity techniques: keep two copies of data in the same mirror set and update the parity block in the log disk within the same parity groups. Reliability analysis shows that the reliability of MP-RAID, in terms of mean time to data loss (MTTDL), is much better than RAID10 and RAID5.

Parity is a popular form of data protection in redundant arrays of inexpensive/independent disks (RAID) . RAID5 dedicates one out of N disks to parity to mask single disk failures, that is, the contents of a block on a failed disk can be reconstructed by exclusive-ORing the corresponding blocks on surviving disks. RAID5 can mask a single disk failure, and it is vulnerable to data loss if a second disk failure occurs. The RAID5 rebuild process systematically reconstructs the contents of a failed disk on a spare disk, returning the system to its original state, but the rebuild process may be unsuccessful due to unreadable sectors. This has led to two disk failure tolerant arrays (2DFTs) , such as RAID6 based on Reed-Solomon (RS) codes. EVENODD, RDP (Row-Diagonal-Parity), the X-code, and RM2 (Row-Matrix) are 2DFTs with parity coding. RM2 incurs a higher level of redundancy than two disks, while the X-code is limited to a prime number of disks. RDP is optimal with respect to the number of XOR operations at the encoding, but not for short write operations. For small symbol sizes EVENODD and RDP have the same disk access pattern as RAID6, while RM2 and the X-code incur a high recovery cost with two failed disks. We describe variations to RAID5 and RAID6 organizations, including clustered RAID, different methods to update parities, rebuild processing, disk scrubbing to eliminate sector errors, and the intra-disk redundancy (IDR) method to deal with sector errors. We summarize the results of recent studies of failures in hard disk drives. We describe Markov chain reliability models to estimate RAID mean time to data loss (MTTDL) taking into account sector errors and the effect of disk scrubbing. Numerical results show that RAID5 plus IDR attains the same MTTDL level as RAID6, while incurring a lower performance penalty. We conclude with a survey of analytic and simulation studies of RAID performance and tools and benchmarks for RAID performance evaluation.

High performance, highly reliable, and energy-efficient storage systems are essential for mobile data-intensive applications such as remote surgery and mobile data center. Compared with conventional stationary storage systems, mobile disk-array-based storage systems are more prone to disk failures due to their severe application environments. Further, they have a very limited power supply. Therefore, data reconstruction algorithms which are executed in the presence of disk failure for mobile storage systems must be performance-driven, reliability-aware, and energy-efficient. Unfortunately, existing reconstruction schemes cannot fulfill these three goals simultaneously because they largely overlook the fact that mobile disks have much higher failure rates than stationary disks. Besides, they normally ignore energy saving. In this paper, we develop a novel reconstruction strategy, called multilevel caching-based reconstruction optimization (MICRO), which can be applied to RAID-structured mobile storage systems to noticeably shorten reconstruction times and user response times while saving energy. MICRO collaboratively utilizes storage cache and disk array controller cache to diminish the number of physical disk accesses caused by reconstruction. Experimental results demonstrate that, compared with two representative algorithms, DOR and PRO, MICRO reduces reconstruction times on average by 20.22 percent and 9.34 percent, while saving energy by no less than 30.4 percent and 13 percent, respectively.

Network attached storage (NAS) integrates redundant array of independent disks (RAID) subsystem that consists of multiple disk drives to aggregate storage capacity, I/O performance and reliability based on data striping and distribution. Traditionally, the stripe size is an important parameter that has a great influence on the RAID subsystem performance, whereas the performance impact has been changed due to the development of disk drive technologies and some I/O optimization methods. Based on disk drive access time, this paper constructs a performance analysis model to exploit the impact of some I/O optimization approaches including sub-commands combination, storage interface augment, and I/O scatter/gather on the stripe size of NAS. The analysis results and experimental validation indicate that due to the evolution of hardware and software, the stripe size has a negligible performance impact on NAS when the disk drives involved are organized in a RAID0 pattern.

This paper proposes an efficient parity placement scheme, Horizontal-Oblique Parity (HOP), for protecting against double disk failures in RAID-5 disk array systems. It keeps all data unencoded, and uses only exclusive-or (XOR) operations to compute parity. HOP is provably near optimal in computational complexity, both during construction and reconstruction. It is optimal in the amount of redundant information stored and is sub-optimal in its accessing. HOP works within a single stripe of blocks of sizes normally used by file systems, databases, and disk arrays.

Server storage systems use a large number of disks to achieve high performance, thereby consuming a significant amount of power. In this paper, we propose to significantly reduce the power consumed by such storage systems via intra-disk parallelism, wherein disk drives can exploit parallelism in the I/O request stream. Intra-disk parallelism can facilitate replacing a large disk array with a smaller one, using the minimum number of disk drives needed to satisfy the capacity requirements. We show that the design space of intra-disk parallelism is large and present a taxonomy to formulate specific implementations within this space. Using a set of commercial workloads, we perform a limit study to identify the key performance bottlenecks that arise when we replace a storage array that is tuned to provide high performance with a single high-capacity disk drive. We show that it is possible to match, and even surpass, the performance of a storage array for these workloads by using a single disk drive of sufficient capacity that exploits intra-disk parallelism, while significantly reducing the power consumed by the storage system. We evaluate the performance and power consumption of disk arrays composed of intra-disk parallel drives, and discuss engineering and cost issues related to the implementation and deployment of such disk drives.

RAID5 tolerates single disk failures by exclusive-ORing (XORing) the blocks corresponding to a requested block on the failed disk to reconstruct it. This results in increased loads on surviving disks and degraded disk response times with respect to normal mode operation. Provided a spare disk is available, a rebuild process systematically reads successive disk tracks, XORs them to recreate lost tracks and writes them onto a spare disk, thus returning the system to its original state. Rebuild time is important since RAID5 disk arrays with a single disk failure are susceptible to data loss if a second disk fails. According to the vacationing server model (VSM), rebuild read requests on surviving disks are given a lower priority than external user requests, so as to have less impact on their response time. Given that disk loads are balanced due to striping, rebuild time can be approximated by the time to read the contents of any one of the surviving disks. The analysis of the M/G/1 queueing model of VSM, given in this article, is more accurate and yet simpler than a previous analysis, but it also takes into account the effect of disk zoning explicitly. We also present a heuristic method to estimate rebuild time, which can be combined with the new analysis. The ability to quickly and accurately estimate rebuild time is useful in computing the reliability of RAID5 systems, especially during design tradeoff studies. The accuracy of the various analyses to estimate rebuild time are checked against detailed simulation results.

Because of the huge advantage of RAID technology in storage, it has been widely used. However, the question associated with this technology is that the hard disk based on the RAID card can not be queried by Operating System. Therefore how to read the self-information and log data of hard disk has been a problem, while this data is necessary for reliability test of hard disk. In traditional way, this information can be read just suitable for SATA hard disk, but not for SAS hard disk. In this paper, we provide a method by using LSI RAID card’s Application Program Interface, communicating with RAID card and analyzing the feedback data to solve the problem. Then we will get the necessary information to assess the SAS hard disk.