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Fuzzy Reliability Analysis of an iSCSI-Based Fault Tolerant storage system Organization

Fuzzy Reliability Analysis of an iSCSI-Based Fault Tolerant ...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： MingHua Jiang Jingli Zhou Ming Hu College of Computer Science & Technology Wuhan University of Science and Engineering Wuhan China Key Laboratory of Data Storage System Ministry of Education Huazhong University of Science and Technology Wuhan China

ISCSI is a newly emerging protocol with the goal of implementing the storage area network (SAN) technology over TCP/IP, which brings economy and convenience whereas it also raises performance and reliability issues. This paper presents a implementation of iSCSTbased fault tolerant storage system, and then analyzed the reliability of this system by combination of fuzzy logic and Markov modeling. This reliability method is a technique for analyzing fault tolerant designs under considerable uncertainty, such as is seen in compilations of component failure rates, the presented model provides the estimation of the lower and upper boundary of iSCSTbased fault tolerant storage system with a single run of the model.

关键词： Fuzzy systems Fault tolerant systems storage area networks Network servers Switches Fault tolerance Local area networks Laboratories Educational technology Protocols

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Fuzzy Reliability of Mirrored Disk Organizations

Fuzzy Reliability of Mirrored Disk Organizations

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International Conference on Convergence Information Technology

作者： MingHua Jiang Jingli Zhou Ming Hu YiXiang Ding College of Computer Science &Technology Wuhan University of Science and Engineering Wuhan China Key Laboratory of Data Storage System Huazhong University of Science슠and슠Technology Wuhan China

Disk mirroring or RAID1 is a popular paradigm to achieve fault tolerance and high reliability, this paper describes four mirrored disk organizations: basic mirroring, group rotate declustering, interleaved declustering, chained declustering, then the membership function of the states is defined and the reliability of mirrored disk system is analyzed by using the reliability theory based on fuzzy state.

关键词： Reliability theory Fuzzy systems Fuzzy set theory Reliability engineering Risk analysis Information technology Information analysis Educational institutions Computer science Laboratories

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BlzFS: Crash Consistent Log-structured File system Based on Byte-loggable Zone for ZNS SSD

BlzFS: Crash Consistent Log-structured File System Based on ...

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IEEE International Conference on Computer Design: VLSI in Computers and Processors, (ICCD)

作者： Wenjie Qi Zhipeng Tan Ziyue Zhang Jing Zhang Chao Yu Ying Yuan Shikai Tan Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China School of Computer Science & Technology Huazhong University of Science & Technology Guangdong Oppo Mobile Telecommunications Corp. Ltd

Emerging Zoned Namespace (ZNS) SSDs provide hosts with fine-grained, performance-predictable storage management. The ZNS SSD divides its address space into zones, and each zone must be written sequentially and cannot be overwritten. However, the write constraint results in frequent small modifications of file metadata to record the latest logical block addresses of the updated data blocks, increasing the overhead of fsync() system call. We comprehensively analyze the metadata overhead of fsync on a real ZNS SSD and find that (1) the update size of most metadata blocks (e.g., tens of bytes) is far less than the IO unit of the zone (e.g., 4 KiB), and frequent fsyncs cause severe metadata write amplification; (2) metadata block IOs significantly increase the fsync latency, decreasing the throughput of *** reduce the metadata overhead of fsync, we build the byte-loggable zone based on the persistent write cache of the opened zone, a novel extension of ZNS, which can be appended at byte granularity instead of block. Based on the byte-loggable zone, we present BlzFS, a high-performance and crash-consistent file system for ZNS SSD. Firstly, BlzFS maintains the update ranges of the metadata block by the update bitmap. Secondly, BlzFS ensures the persistence and consistency of metadata by logging the partial updates of metadata blocks to the device’s byte-loggable zone. Finally, BlzFS restores metadata consistency by replaying the metadata update log and scanning the list of recent allocated metadata blocks. In the evaluation, BlzFS shows a 33.5%∼96.1% reduction in metadata write traffic and a 1.37×∼1.91× throughput improvement compared with the original ZNS storage system.

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EvoRAID: Adaptation to Dynamic Change of Disks in storage system

EvoRAID: Adaptation to Dynamic Change of Disks in Storage Sy...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Yan Liu Chang-Sheng Xie Huai-Yang Li Zhao-bin Liu Key Laboratory of Data Storage System School of Computer Science and Technology Huazhong University of Science and Technology Wuhan Hubei China School of Computer Science and Technology Dalian Maritime University China

The system architecture cannot adapt to the dynamic change of system disks, which is a general problem in traditional storage system. While EvoRAID system, a dynamic storage system we proposed, applies DAA algorithm to cope with three kinds of storage system disk changes - homogeneous disk adding, heterogeneous disk adding, and heterogeneous disk replacement. Simulation results demonstrate that without stopping system I/O service, EvoRAID system can assimilate the adding/replacing homogeneous/heterogeneous disks gradually with little extra system overhead, and achieve optimized storage capacity and I/O performance.

关键词： Computer architecture Heuristic algorithms Distributed databases Process control Software Arrays Bandwidth

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Seastar: A Cache-Efficient and Load-Balanced key-Value Store on Disaggregated Memory

Seastar: A Cache-Efficient and Load-Balanced Key-Value Store...

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IEEE International Conference on Cluster Computing

作者： Jingwen Du Fang Wang Dan Feng Dexin Zeng Sheng Yi Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China China School of Computer Science and Technology Huazhong University of Science and Technology China Shenzhen Huazhong University of Science and Technology Research Institute China

ISBN: (数字)9798350358711

ISBN: (纸本)9798350358728

In modern datacenters, memory disaggregation un-packs monolithic servers to build independent network-connected compute and memory pools, greatly improving resource uti-lization. Existing memory-disaggregated key-value stores adopt ownership sharing or ownership partitioning for request scheduling and they all show poor performance and scalability. The former generates multiple cache misses and multiple network round trips due to poor cache locality, while the latter fails to fully use resources on all Compute Nodes (CNs) due to load imbalance. In this paper, we propose Seastar, a fast and scalable key-value store that achieves high cache locality as well as load balancing. To enable high concurrency and ensure linearizability, Seastar exploits a self-verification version chain to provide out-of-place atomic updates and ensure consistent reads. To improve cache locality, Seastar leverages a pair-based ownership assigning scheme to assign the processing permission of requests corre-sponding to each key to a CN pair through two independent hash functions. To ensure load balancing among CNs, Seastar proposes a decentralized power-of-two-choices routing scheme to route the requests to the less-loaded CNs in CN pairs for handling. Experimental results demonstrate that Seastar improves the throughput by up to 6.7x and significantly reduces the latency compared with state-of-the-art memory-disaggregated key-value stores.

关键词： Concurrent computing Hash functions Protocols Processor scheduling Scalability Cluster computing Load management Throughput Routing Servers

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Scavenger: Better Space-Time Trade-Offs for key-Value Separated LSM-trees

Scavenger: Better Space-Time Trade-Offs for Key-Value Separa...

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International Conference on data Engineering

作者： Jianshun Zhang Fang Wang Sheng Qiu Yi Wang Jiaxin Ou Junxun Huang Baoquan Li Peng Fang Dan Feng Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of data storage systems and Technology Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology China Shenzhen Huazhong University of Science and Technology Research Institute Bytefrance Inc.

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

key- Value Stores (KVS) implemented with log- structured merge-tree (LSM-tree) have gained widespread ac-ceptance in storage systems. Nonetheless, a significant challenge arises in the form of high write amplification due to the compaction process. While KV-separated LSM-trees successfully tackle this issue, they also bring about substantial space am-plification problems, a concern that cannot be overlooked in cost-sensitive scenarios. Garbage collection (GC) holds significant promise for space amplification reduction, yet existing GC strategies often fall short in optimization performance, lacking thorough consideration of workload characteristics. Additionally, current KV-separated LSM-trees also ignore the adverse effect of the space amplification in the index LSM-tree. In this paper, we systematically analyze the sources of space amplification of KV- separated LSM-trees and introduce Scavenger, which achieves a better trade-off between performance and space amplification. Scavenger initially proposes an I/O-efficient garbage collection scheme to reduce I/O overhead and incorporates a space-aware compaction strategy based on compensated size to minimize the space amplification of index LSM-trees. Extensive experiments show that Scavenger significantly improves write performance and achieves lower space amplification than other KV-separated LSM-trees (including BlobDB, Titan, and TerarkDB).

关键词： data engineering Compaction Indexes Optimization

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Metadata Management for Distributed Multimedia storage system

Metadata Management for Distributed Multimedia Storage Syste...

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International Symposium on Electronic Commerce and Security

作者： Ling Zhan Jiguang Wan Peng Gu Key Laboratory of Data Storage System School of Computer Science and Technology Huazhong University of Science and Technology Wuhan Hubei China School of Electrical Engineering and Computer Science University of Central Florida Orlando FL USA

ISBN: (纸本)9780769532585

As a result of the multimedia rapid growth, there has been a huge increase in the amount of information generated and shared by people all over the world. Demand for large-scale multimedia storage system is growing rapidly. This paper describes the design and implementation of the Two-level metadata server for distributed multimedia storage system (DMSS). The DMSS divides the logical view of the stored data from the physical view. The logical view is managed by the metadata server which is called GMS (global metadata server), and the physical view is managed by a component of storage servers which is called LMS (local metadata server). Adopting LMS, each storage server can maintain its own storage resources and metadata and data independently, and can offer storage service independently. The DMSS allows the application servers to access the storage servers directly and in parallel providing very high performance.

关键词： Servers Multimedia communication Multimedia systems Least squares approximation system performance File systems Heart beat

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FAGC: Free Space Fragmentation Aware GC Scheme based on Observations of Energy Consumption

FAGC: Free Space Fragmentation Aware GC Scheme based on Obse...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Lihua Yang Zhipeng Tan Fang Wang Yang Xiao Wei Zhang Biao He Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology College of Science and Technology National University of Defense Technology China Huawei Technology Co. Ltd China

Smartphones are everyday necessities with limited power supply. Charging a smartphone twice a day or more affects user experience. Flash friendly file system (F2FS) is a widely-used log-structured file system for smartphones. Free space fragmentation of F2FS consists of invalid blocks mainly causing performance degradation. F2FS reclaims invalid blocks by garbage collection (GC). We explore the energy consumption of GC and the effect of GC on reducing free space fragments. We observe the energy consumption of one background GC is large but its effect on reducing free space fragments is limited. These motivate us to improve the energy efficiency of GC. We reassess how much free space is a free space fragment based on data analysis, use the free space fragmentation factor to measure the degree of free space fragmentation quickly. We suggest the free space fragmentation aware GC scheme (FAGC) that optimizes the selection for victim segments and the migration for valid blocks. Experiments on real platform show that FAGC reduces GC count by 82.68% and 74.51% respectively than traditional F2FS and the latest GC optimization of F2FS, ATGC. FAGC reduces the energy consumption by 164.37 J and 100.64 J compared to traditional F2FS and ATGC respectively for a synthetic benchmark.

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Lifelong Disk Failure Prediction via GAN-Based Anomaly Detection

Lifelong Disk Failure Prediction via GAN-Based Anomaly Detec...

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IEEE International Conference on Computer Design: VLSI in Computers and Processors, (ICCD)

作者： Tianming Jiang Jiangfeng Zeng Ke Zhou Ping Huang Tianming Yang Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China School of Computer Science & Technology Huazhong University of Science & Technology China School of Information Management Central China Normal University China Temple University USA Huanghuai University China

As a classical technique in storage systems, disk failure prediction aims at predicting impending disk failures in advance for high data reliability. Over the past decades, taking as input the SMART (Self-Monitoring, Analysis and Reporting Technology) attributes, many supervised machine learning algorithms have been proven to be effective for disk failure prediction. However, these approaches heavily rely on the availability of substantial annotated failed disk data which unfortunately exhibits an extreme data imbalance, i.e., the number of failed disks is much smaller than that of healthy ones, resulting in suboptimal performance and even inability at the beginning of their deployment, i.e., cold starting problem. Inspired by the significant success achieved in GAN (Generative Adversarial Network) based anomaly detection, in this paper, we translate disk failure prediction into an anomaly detection problem. Specifically, we develop a novel Semi-supervised method for lifelong disk failure Prediction via Adversarial training, called SPA. The distinguishing feature of SPA from existing supervised approaches is that SPA is only trained on healthy disks, which avoids the traditional limitations of imbalance in datasets and eliminates the cold starting problem. Furthermore, a novel 2D image-like representation technique is proposed to enable the deployment of deep learning techniques and the automatic feature extraction. Experimental results on real-world SMART datasets demonstrate that, compared with the state-of-the-art supervised machine learning based methods, our approach predicts disk failures at a higher accuracy for the entire lifetime of models, i.e., both the initial period and the long-term usage.

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A Fine-Grained data Reconstruction Algorithm for Solid-State Disks

A Fine-Grained Data Reconstruction Algorithm for Solid-State...

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International Conference on Networking, Architecture, and storage (NAS)

作者： Peng Wang Diqing Hu Changsheng Xie Jianzong Wang Xiao Qin Wuhan National Laboratory of Optoelectronics Key Laboratory of Data Storage System Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology Wuhan Hubei China Department of Computer Science and Software Engineering Samuel Ginn College of Engineering Aubum University USA

Solid-state disks (SSDs) with high I/O performance are increasingly becoming popular. To extend the life time of flash memory, one can apply wear-leveling strategies to manage data blocks. However, wear-leveling strategies certainly inevitably degrade write performance. In addition to low write performance, wear-leveling strategies make one block unwritable when one bit of this block is invalid. Although data reconstruction techniques have been widely employed in disk arrays, the reconstruction techniques has not been studied in the context of solid-state disks. In this paper, we present a new fine-grained data-reconstruction algorithm for solid-state disks. The algorithm aims to provide a simple yet efficient wear-leveling strategy that improves both I/O performance and reliability of solid-state disks. Simulation experiments show that all data blocks have very similar in terms of erasure times. The number of extra erasures incurred by our algorithm is very marginal.

关键词： Reconstruction algorithms Reliability Mathematical model Flash memory Equations Arrays Parity check codes

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