Redundant Array Of Independent Disks Research Articles

Experimental investigation of the polyhedral structure of BIBDs

We examine the polyhedral structure of Balanced Incomplete Block Designs (BIBDs) in an effort to improve runtimes for finding optimal solutions via constraint or integer program. For example, an optimal BIBD is one that minimizes the range of blocksums. This range, which we refer to as diffsum, has applications in drug trials and Redundant Arrays of Independent Disks (RAID). The polytope we explore is the convex hull of all lexicographically-ordered BIBD solutions satisfying a given set of parameters, ( v , b , r , k , λ ) , with solutions represented as a vector in R kb . The dimension-reducing equations and the facets for some of the smaller polytopes were found by using the Double-Description Method on a algebraic program modelling these solutions. Because of the presence of the lexicographic ordering, none of these polytopes are full dimensional. After describing some of these smaller BIBD polytopes, we generalize some dimension-reducing equations, and evaluate the efficiency of these equations to optimization models.

Triple-Disk Recovery RDP Coding: A Robust Solution for Data Storage in RAID Configurations

Data-intensive technologies require reliable and efficient storage solutions to ensure the integrity and availability of vast amounts of generated data. Redundant Arrays of Independent Disks (RAID) technology has emerged as a popular choice, offering fault tolerance and improved performance. Among RAID configurations, RAID-6 stands out for its ability to tolerate up to two disk failures. This is achieved through algorithms like Row-Diagonal Parity (RDP) coding, which introduces redundancy and enables data recovery. In this paper, we propose an innovative approach, namely Triple-Disk Recovery RDP (TDR-RDP), to enhance reliability based on RDP coding by accommodating three disk failures. We review the RDP algorithm, introduce the TDR-RDP coding scheme, elaborate on encoding and decoding processes, and address diverse types of triple disk failures along with their recovery strategies. Furthermore, we evaluate and compare the computing efficiency of TDR-RDP with the RDP algorithm, showcasing its practical feasibility. Overall, the TDR-RDP algorithm offers a compelling solution to bolster data storage reliability in RAID configurations, surpassing traditional RDP coding by ensuring resilience against triple disk failures and augmenting data-intensive technologies.

H[formula omitted]-RAID: Improving the reliability of SSD RAID with unified SSD and HDD hybrid architecture

With the increasing development of SSD (Solid-State Drives) technology, SSD RAID (Redundant Arrays of Independent Disks) has been widely deployed in enterprise data centers. However, the inherent write endurance issue of SSD seriously affects the reliability of the array. Meanwhile, compared with conventional HDD-based RAID, SSD RAID exhibits very different failure characteristics, such as correlated failure (Balakrishnan et al., 2010) under RAID-5. In this paper, we present a Hybrid High reliability RAID architecture, named H2-RAID, by equipping each SSD with an extra HDD as the backup to improve the reliability of SSD RAID. Considering the relatively longer write latency of HDD, in H2-RAID, we first propose an HDD-aware backup mechanism to smartly aggregate random writes into sequential writes to decrease performance degradation. In addition, to cope with the scenarios of SSD failure, an HDD-aware reconstruction method is further proposed to guarantee the reliability and the online transaction processing performance. We build a novel Markov process-based mathematical model to analyze the reliability of different architectures, and the theoretical results prove the reliability of H2-RAID is much higher than that of traditional SSD RAID. To more accurately evaluate the performance influence of HDD on H2-RAID, we develop a simulator based on Disksim and the experimental results show H2-RAID significantly increases the reliability compared with SSD array (under RAID-5) while with little performance loss on average.

Efficient Reed–Solomon Redundant Arrays of Independent Disks 6 Exclusive OR Accelerator with Scaling Scheme

Efficient Reed–Solomon Redundant Arrays of Independent Disks 6 Exclusive OR Accelerator with Scaling Scheme

Graph-Based Replication and Two Factor Authentication in Cloud Computing

Many cutting-edge methods are now possible in real-time commercial settings and are growing in popularity on cloud platforms. By incorporating new, cutting-edge technologies to a larger extent without using more infrastructures, the information technology platform is anticipating a completely new level of development. The following concepts are proposed in this research paper: 1) A reliable authentication method Data replication that is optimised; graph-based data encryption and packing colouring in Redundant Array of Independent Disks (RAID) storage. At the data centre, data is encrypted using crypto keys called Key Streams. These keys are produced using the packing colouring method in the web graph’s jump graph. In order to achieve space efficiency, the replication is carried out on optimised many servers employing packing colours. It would be thought that more connections would provide better authentication. This study provides an innovative architecture with robust security, enhanced authentication, and low cost.

The Cyber Attack on Saudi Aramco in 2012

In recent years, information security has become a corporate priority due tothe large number of cyber-attacks that happen every day. These attacks could cause a regression in economic growth, which makes corporations another reason to defend their system. This paper provides an introduction to Saudi Aramco as well as an overview of its products. Then, the paper examines the Aramco cyber-attack in 2012. Aramco is a massive company with huge facilities that require powerful policies on security. Aramco should implement a Redundant Array of Independent Disks and Intrusion Detection System and review the log files on the server to protect its servers against attacks.

Performance Evaluations of Distributed File Systems for Scientific Big Data in FUSE Environment

Data are important and ever growing in data-intensive scientific environments. Such research data growth requires data storage systems that play pivotal roles in data management and analysis for scientific discoveries. Redundant Array of Independent Disks (RAID), a well-known storage technology combining multiple disks into a single large logical volume, has been widely used for the purpose of data redundancy and performance improvement. However, this requires RAID-capable hardware or software to build up a RAID-enabled disk array. In addition, it is difficult to scale up the RAID-based storage. In order to mitigate such a problem, many distributed file systems have been developed and are being actively used in various environments, especially in data-intensive computing facilities, where a tremendous amount of data have to be handled. In this study, we investigated and benchmarked various distributed file systems, such as Ceph, GlusterFS, Lustre and EOS for data-intensive environments. In our experiment, we configured the distributed file systems under a Reliable Array of Independent Nodes (RAIN) structure and a Filesystem in Userspace (FUSE) environment. Our results identify the characteristics of each file system that affect the read and write performance depending on the features of data, which have to be considered in data-intensive computing environments.

An Empirical Performance Evaluation of Multiple Intel Optane Solid-State Drives

Cloud computing as a service-on-demand architecture has grown in importance over the last few years. The storage subsystem in cloud computing has undergone enormous innovation to provide high-quality cloud services. Emerging Non-Volatile Memory Express (NVMe) technology has attracted considerable attention in cloud computing by delivering high I/O performance in latency and bandwidth. Specifically, multiple NVMe solid-state drives (SSDs) can provide higher performance, fault tolerance, and storage capacity in the cloud computing environment. In this paper, we performed an empirical evaluation study of performance on recent NVMe SSDs (i.e., Intel Optane SSDs) with different redundant array of independent disks (RAID) environments. We analyzed multiple NVMe SSDs with RAID in terms of different performance metrics via synthesis and database benchmarks. We anticipate that our experimental results and performance analysis will have implications for various storage systems. Experimental results showed that the software stack overhead reduced the performance by up to 75%, 52%, 76%, 91%, and 92% in RAID 0, 1, 10, 5, and 6, respectively, compared with theoretical and expected performance.

Survivability and Vulnerability Analysis of Cloud RAID Systems under Disk Faults and Attacks

In this paper we model and analyze survivability and vulnerability of a cloud RAID (Redundant Array of Independent Disks) storage system subject to disk faults and cyber-attacks. The cloud RAID survivability is concerned with the system’s ability to function correctly even under the circumstance of hazardous behaviors including disk failures and malicious attacks. The cloud RAID invulnerability is concerned with the system’s ability to function correctly while occupying some state immune to malicious attacks. A continuous-time Markov chains-based method is suggested to perform the disk level survivability and invulnerability analysis. Combinatorial methods are then presented for the cloud RAID system level analysis, which can accommodate both homogeneous (based on binomial coefficients) and heterogeneous (based on multi-valued decision diagrams) disks. A detailed case study on a cloud RAID 5 system is conducted to illustrate the application of the proposed methods. Impacts of different parameters on the disk and system survivability and invulnerability are also investigated through numerical analysis.

A Modeling Framework for Reliability of Erasure Codes in SSD Arrays

To help reliability of SSD arrays, Redundant Array of Independent Disks (RAID) are commonly employed. However, the conventional reliability models of HDD RAID cannot be applied to SSD arrays, as the nature of failures in SSDs are 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 explore 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 injections that post-process the usage logs from the real-system implementation, while the fault/failure attributes are obtained from field data. As a case study, we examine conventional and emerging erasure codes in terms of both reliability and performance using Linux MD RAID and commercial SSDs. Our analysis 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 focus on the coincidence of bad pages and bad chips that roots the minority of Data Loss (DL) in SSD arrays. Our experiments show that the combination of bad chips with bad blocks is the major source of DL in RAID5 and emerging codes (contributing more than 54% and 90% of DL in RAID5 and emerging codes, respectively), while RAID6 remains robust under these failure combinations. Finally, the fault injection results show that SSD array reliability, as well as the failure breakdown is significantly correlated with SSD type.

GC-Steering: GC-Aware Request Steering and Parallel Reconstruction Optimizations for SSD-Based RAIDs

Solid-state disk (SSD)-based redundant array of independent disks (RAIDs) have been widely deployed in high-end enterprize systems to provide high-performance and highly reliable storage for data-intensive computing. However, SSD-based RAIDs suffer from significant performance degradation whenever user I/O requests conflict with the ongoing garbage collection (GC) operations which introduce tail latency. Moreover, the performance characteristics of SSDs make the traditional HDD-based RAID reconstruction algorithms are not compatible with or suitable for SSD-based RAIDs. In this article, we proposed GC-aware request steering (GC-Steering), a scheme aware of the GC process within an SSD-based RAID, to significantly boost the performance and reliability of SSD-based RAIDs. GC-Steering effectively outsources the popular read requests and all write requests addressed to the SSD currently in the GC state to a staging space, such as a dedicated spare SSD or the reserved space of each SSD within the RAID. GC-Steering also accelerates the performance of the failure-recovery process by both request steering and parallel recovery. Our extensive evaluations on a lightweight GC-Steering prototype driven by HPC-like and real-world enterprize workloads show that the GC-Steering scheme significantly reduces the average response time by an average of 63.3% and 65.8%, compared with the state-of-the-art local GC and global GC schemes. Moreover, the GC-Steering scheme also significantly reduces the average response times by an average of 62.3% during RAID reconstruction than the normal state.

Highly Available Nuclear Power for Mission-Critical Applications

Some energy consumers require power on an anytime, all-year-round basis with a high level of certainty, including defense installations, isolated communities, and some industrial processes. For these customers, interruptions in electricity or heat can mean substantial financial loss or even loss of life. In the absence of grid-scale energy storage, a high level of power availability can be accomplished only through the robustness and redundancy of power generators. The NuScale small modular reactor design is well suited to provide highly available power because of several features related to both the nuclear steam supply system and the overall plant design. In analogy to Redundant Array of Independent Disks (RAID) systems used to provide highly reliable data storage, a NuScale plant can assure sustained power generation by virtue of its Redundant Array of Integral Reactors (RAIR).This paper describes the NuScale RAIR plant features and summarizes the results of a rigorous analysis of RAIR availability as a function of power or, conversely, the RAIR plant output power as a function of power availability. The analysis utilized the Matrix Laboratory code (MATLAB) and included probability distributions for the frequency and duration of module outages due to planned and unplanned events. The study also evaluated the impact of implementing turbine bypass rather than module shutdown and using one or more modules to supply house loads in the case of loss of off-site power (LOOP). Availability results are presented for a 12-module RAIR plant with and without turbine bypass enabled during a LOOP and for different possible connections to the off-site power distribution grid and dedicated service loads. Results indicate that a very high level of availability can be achieved at relatively high power output levels, regardless of turbine bypass and dedicated load connection, compared to the operating fleet.

Influence of different factors on the RAID 0 paired magnetic disk arrays

The rapid technological progress has led to a growing need for more data storage space. The appearance of big data requires larger storage space, faster access and exchange of data as well as data security. RAID (Redundant Array of Independent Disks) technology is one of the most cost-effective ways to satisfy needs for larger storage space, data access and protection. However, the connection of multiple secondary memory devices in RAID 0 aims to improve the secondary memory system in a way to provide greater storage capacity, increase both read data speed and write data speed but it is not fault-tolerant or error-free. This paper provides an analysis of the system for storing the data on the paired arrays of magnetic disks in a RAID 0 formation, with different number of queue entries for overlapped I/O, where queue depth parameter has the value of 1 and 4. The paper presents a range of test results and analysis for RAID 0 series for defined workload characteristics. The tests were carried on in Microsoft Windows Server 2008 R2 Standard operating system, using 2, 3, 4 and 6 paired magnetic disks and controlled by Dell PERC 6/i hardware RAID controller. For the needs of obtaining the measurement results, ATTO Disk Benchmark has been used. The obtained results have been analyzed and compared to the expected behavior.

Design and Implementation of SSD-Assisted Backup and Recovery for Database Systems

As flash-based solid-state drive (SSD) becomes more prevalent because of the rapid fall in price and the significant increase in capacity, customers expect better data services than traditional disk-based systems. However, the order of magnitude performance provided and new characteristics of flash require a rethinking of data services. For example, backup and recovery is an important service in a database system since it protects data against unexpected hardware and software failures. To provide backup and recovery, backup/recovery tools or backup/recovery methods by operating systems can be used. However, the tools perform time-consuming jobs, and the methods may negatively affect run-time performance during normal operation even though high-performance SSDs are used. To handle these issues, we propose an SSD-assisted backup/recovery scheme for database systems. Our scheme is to utilize the characteristics (e.g., out-of-place update) of flash-based SSD for backup/recovery operations. To this end, we exploit the resources (e.g., flash translation layer and DRAM cache with supercapacitors) inside SSD, and we call our SSD with new backup/recovery functionality BR-SSD. We design and implement the functionality in the Samsung enterprise-class SSD (i.e., SM843Tn) for more realistic systems. Furthermore, we exploit and integrate BR-SSDs into database systems (i.e., MySQL) in replication and redundant array of independent disks (RAID) environments, as well as a database system in a single BR-SSD. The experimental result demonstrates that our scheme provides fast backup and recovery but does not negatively affect the run-time performance during normal operation.

Balancing Reliability and Cost in Cloud-RAID Systems with Fault-Level Coverage

Based on redundancy techniques, cloud-RAIDs (Redundant Array of Independent Disks) offer an effective storage solution to achieve high data reliability. Their performance however can be greatly hindered by the fault-level coverage (FLC) behavior, where an uncovered disk fault may crash the entire system in spite of adequate redundancy remaining. Moreover, different choices of cloud disk providers lead to designs with different overall reliability and cost. Thus, in this paper we formulate and solve optimization problems, which determine the combination of cloud disks (from different providers) maximizing the cloud-RAID system reliability or minimizing the total cost. The cloud-RAID reliability is analyzed using a combinatorial and analytical modeling method while considering effects of the FLC behavior. Multiple case studies are performed to demonstrate the considered optimization problems and proposed solution methodology.

Fault‐level coverage analysis of multistate cloud‐RAID storage systems

In this paper, a multistate cloud‐RAID (redundant array of independent disks) storage system subject to fault‐level coverage (FLC) is modeled and analyzed. Most of the existing works on reliability analysis of cloud‐RAID systems have either assumed binary‐state for storage disks or failed to consider imperfect fault coverage, an inherent behavior of fault‐tolerant systems. This work advances the state of the art by proposing a combinatorial method based on multivalued decision diagrams for analyzing reliability of a multistate cloud‐RAID system with FLC. The FLC is one common type of imperfect fault coverage behaviors, where the system fault recovery capability is dependent on the number of disk faults happening within a certain recovery window. Effects of the functional dependence behavior between the RAID controller and disks are addressed. The method is illustrated through a detailed analysis of an example cloud‐RAID 5 storage system. Numerical results are provided to show the impact of different design parameters on system performance. These results also demonstrate that failure to consider FLC leads to inaccurate system state probabilities, further misleading system design activities based on these probabilities such as maintenance and optimization.

Popularity-Based Online Scaling for RAID Systems Under General Settings

The ever-increasing demand of storage capacity and system performance leads to the scaling requirement in redundant arrays of independent disks (RAID)-structured storage systems. Existing approaches mainly focus on minimizing data migration in offline scenario, but not consider the user accesses issued by applications. However, in online scenario, the scaling I/Os and user I/Os usually interfere with each other, and result in significant performance degradation. Thus, it is of big significance to develop an efficient online scaling scheme to mitigate the impact of I/O interference. In this paper, we propose popularity-based online scaling (POS), which exploits workload locality by scaling storage zones with high popularity in a higher priority. POS can efficiently alleviate the interference between scaling I/Os and user I/Os, and it is also general enough to scale various RAID systems like RAID-0, RAID-5, and RAID-6. It can also be readily deployed atop various conventional RAID scaling approaches to improve their performance. To demonstrate the effectiveness of POS, we implement various conventional RAID scaling approaches, and also implement POS on top of these approaches for comparison. Extensive simulations with real-world workloads show that POS can efficiently reduce the response time of user requests and scaling I/Os, and also improves the sequentiality of data accesses.

RAID 4SMR: RAID Array with Shingled Magnetic Recording Disk for Mass Storage Systems

One way to increase storage density is using a shingled magnetic recording (SMR) disk. We propose a novel use of SMR disks with RAID (redundant array of independent disks) arrays, specifically building upon and compared with a basic RAID 4 arrangement. The proposed scheme (called RAID 4SMR) has the potential to improve the performance of a traditional RAID 4 array with SMR disks. Our evaluation shows that compared with the standard RAID 4, when using update in-place in RAID arrays, RAID 4SMR with garbage collection not just can allow the adoption of SMR disks with a reduced performance penalty, but offers a performance improvement of up to 56%.

Classified enhancement model for big data storage reliability based on Boolean satisfiability problem

Disk reliability is a serious problem in the big data foundation environment. Although the reliability of disk drives has greatly improved over the past few years, they are still the most vulnerable core components in the server. If they fail, the result can be catastrophic: it can take some days to recover data, sometimes data lost forever. These are unacceptable for some important data. XOR parity is a typical method to generate reliability syndrome, thus improving the reliability of the data. In practice, we find that the data is still likely to be lost. In most storage systems reliability improvements are achieved through the allocation of additional disks in Redundant Arrays of Independent Disks (RAID), which will increase the hardware costs, thus it will be very difficult for cost-constrained environments. Therefore, how to improve the data integrity without raising the hardware cost has aroused much interest of big data researchers. This challenge is when creating non-traditional RAID geometries, care must be taken to respect data dependence relationships to ensure that the new RAID strategy improves reliability, which is a NP-hard problem. In this paper, we present an approach for characterizing these challenges using high-dimension variants of the n-queens problem that enables performable solutions via the SAT solver MiniSAT, and use the greedy algorithm to analyze the queen’s attack domain, as a basis for reliability syndrome generation. A large number of experiments show that the approach proposed in this paper is feasible in software-defined data centers and the performance of the algorithm can meet the current requirements of the big data environment.

Joint Decoder Design for SSDs

Error-correction codes (ECC) and redundant array of independent disks (RAID) are commonly used to protect NAND-based solid state drives (SSD) from serious noise/disturb. In order to tolerate more errors, common solutions are more complex ECCs and RAIDs. Meanwhile, due to the error-correction mechanisms and flash translation layer, NAND-based SSDs inevitably generate abundant redundant information. The theme of this paper is to show that instead of designing new error correction mechanisms from scratch, the NAND-based SSD reliability can be greatly improved by utilizing current decoders to explore the inherent information between redundant pages. We first propose a joint decoder to recover multiple pages by utilizing redundant pages within a stripe of ECC/RAID, and then we consider a joint decoder to recover multiple pages by utilizing write-amplified (WA) pages. The simulation results show that with the proposed algorithm, a performance gain of as much as 1.8 dB can be obtained. The theoretical study reveals that the joint decoding model can be studied from the perspective of relay channel model, and this helps to explore how much information can be reliably stored with the RAID/WA system in SSD.