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检索条件"任意字段=Proceedings of the 15th Usenix Conference on File and Storage Technologies"

共 435 条记录，以下是151-160 订阅

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Redundancy Does Not Imply Fault Tolerance: Analysis of Distributed storage Reactions to Single Errors and Corruptions 15

Redundancy Does Not Imply Fault Tolerance: Analysis of Distr...

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15th usenix conference on file and storage technologies (FAST)

作者： Ganesan, Aishwarya Alagappan, Ramnatthan Arpaci-Dusseau, Andrea C. Arpaci-Dusseau, Remzi H. Univ Wisconsin Madison Madison WI 53706 USA

ISBN: (纸本)9781931971362

We analyze how modern distributed storage systems behave in the presence of file-system faults such as data corruption and read and write errors. We characterize eight popular distributed storage systems and uncover numerous bugs related to file-system fault tolerance. We find that modern distributed systems do not consistently use redundancy to recover from file-system faults: a single file-system fault can cause catastrophic outcomes such as data loss, corruption, and unavailability. Our results have implications for the design of next generation fault-tolerant distributed and cloud storage systems.

关键词： Redundancy

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Cluster storage systems gotta have HeART: improving storage efficiency by exploiting disk-reliability heterogeneity 19

Cluster storage systems gotta have HeART: improving storage ...

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proceedings of the 17th usenix conference on file and storage technologies

作者： Saurabh Kadekodi K. V. Rashmi Gregory R. Ganger Carnegie Mellon University

ISBN: (纸本)9781931971485

Large-scale cluster storage systems typically consist of a heterogeneous mix of storage devices with significantly varying failure rates. Despite such differences among devices, redundancy settings are generally configured in a one-scheme-for-all fashion. In this paper, we make a case for exploiting reliability heterogeneity to tailor redundancy settings to different device groups. We present HeART, an online tuning tool that guides selection of, and transitions between redundancy settings for long-term data reliability, based on observed reliability properties of each disk group. By processing disk failure data over time, HeART identifies the boundaries and steady-state failure rate for each deployed disk group (e.g., by make/model). Using this information, HeART suggests the most space-efficient redundancy option allowed that will achieve the specified target data reliability. Analysis of longitudinal failure data for a large production storage cluster shows the robustness of HeART's failure-rate determination algorithms. the same analysis shows that a storage system guided by HeART could provide target data reliability levels with fewer disks than one-scheme-for-all approaches: 11-16% fewer compared to erasure codes like 10-of-14 or 6-of-9 and 33% fewer compared to 3-way replication.

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Reaping the performance of fast NVM storage with udepot 19

Reaping the performance of fast NVM storage with udepot

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proceedings of the 17th usenix conference on file and storage technologies

作者： Kornilios Kourtis Nikolas Ioannou Ioannis Koltsidas IBM Research Zurich Google and IBM Research Zurich

ISBN: (纸本)9781931971485

Many applications require low-latency key-value storage, a requirement that is typically satisfied using key-value stores backed by DRAM. Recently, however, storage devices built on novel NVM technologies offer unprecedented performance compared to conventional SSDs. A key-value store that could deliver the performance of these devices would offer many opportunities to accelerate applications and reduce costs. Nevertheless, existing key-value stores, built for slower SSDs or HDDs, cannot fully exploit such *** this paper, we present uDepot, a key-value store built bottom-up to deliver the performance of fast NVM block-based devices. uDepot is carefully crafted to avoid inefficiencies, uses a two-level indexing structure that dynamically adjusts its DRAM footprint to match the inserted items, and employs a novel task-based IO run-time system to maximize performance, enabling applications to use fast NVM devices at their full potential. As an embedded store, uDepot's performance nearly matches the raw performance of fast NVM devices both in terms of throughput and latency, while being scalable across multiple devices and cores. As a server, uDepot significantly outperforms state-of-the-art stores that target SSDs under the YCSB benchmark. Finally, using a Memcache service on top of uDepot we demonstrate that data services built on NVM storage devices can offer equivalent performance to their DRAM-based counterparts at a much lower cost. Indeed, using uDepot we have built a cloud Memcache service that is currently available as an experimental offering in the public cloud.

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Algorithms and Data Structures for Efficient Free Space Reclamation in WAFL 15

Algorithms and Data Structures for Efficient Free Space Recl...

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15th usenix conference on file and storage technologies (FAST)

作者： Kesavan, Ram Singh, Rohit Grusecki, Travis Patel, Yuvraj Netapp Madison NJ USA Univ Wisconsin Madison Madison NJ USA

ISBN: (纸本)9781931971362

NetApp (R) WAFL (R) is a transactional file system that uses the copy-on-write mechanism to support fast write performance and efficient snapshot creation. However, copy-on-write increases the demand on the file system to find free blocks quickly;failure to do so may impede allocations for incoming writes. Efficiency is also important, because the task may consume CPU and other resources. In this paper, we describe the evolution (over more than a decade) of WAFL's algorithms and data structures for reclaiming space with minimal impact on the overall storage appliance performance.

关键词： Digital storage

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Fast erasure coding for data storage: a comprehensive study of the acceleration techniques 19

Fast erasure coding for data storage: a comprehensive study ...

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proceedings of the 17th usenix conference on file and storage technologies

作者： Tianli Zhou Chao Tian Texas A&M University

ISBN: (纸本)9781931971485

Various techniques have been proposed in the literature to improve erasure code computation efficiency, including optimizing bitmatrix design, optimizing computation schedule, common XOR operation reduction, caching management techniques, and vectorization techniques. these techniques were largely proposed individually previously, and in this work, we seek to use them jointly. In order to accomplish this task, these techniques need to be thoroughly evaluated individually, and their relation better understood. Building on extensive test results, we develop methods to systematically optimize the computation chain together with the underlying bitmatrix. this led to a simple design approach of optimizing the bitmatrix by minimizing a weighted cost function, and also a straightforward erasure coding procedure: use the given bitmatrix to produce the computation schedule, which utilizes both the XOR reduction and caching management techniques, and apply XOR level vectorization. this procedure can provide a better performance than most existing techniques, and even compete against well-known codes such as EVENODD, RDP, and STAR codes. Moreover, the result suggests that vectorizing the XOR operation is a better choice than directly vectorizing finite field operations, not only because of the better encoding throughput, but also its minimal migration efforts onto newer CPUs.

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Knockoff: Cheap versions in the cloud 15

Knockoff: Cheap versions in the cloud

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15th usenix conference on file and storage technologies (FAST)

作者： Dou, Xianzheng Chen, Peter M. Flinn, Jason Univ Michigan Ann Arbor MI 48109 USA

ISBN: (纸本)9781931971362

Cloud-based storage provides reliability and ease-of-management. Unfortunately, it can also incur significant costs for both storing and communicating data, even after using techniques such as chunk-based deduplication and delta compression. the current trend of providing access to past versions of data exacerbates both costs. In this paper, we show that deterministic recomputation of data can substantially reduce the cost of cloud storage. Borrowing a well-known dualism from the fault-tolerance community, we note that any data can be equivalently represented by a log of the nondeterministic inputs needed to produce that data. We design a file system, called Knockoff, that selectively substitutes nondeterministic inputs for file data to reduce communication and storage costs. Knockoff compresses both data and computation logs: it uses chunk-based deduplication for file data and delta compression for logs of nondeterminism. In two studies, Knockoff reduces the average cost of sending files to the cloud without versioning by 21% and 24%;the relative benefit increases as versions are retained more frequently.

关键词： Cloud storage

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High-Performance Metadata Integrity Protection in the WAFL Copy-on-Write file System 15

High-Performance Metadata Integrity Protection in the WAFL C...

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15th usenix conference on file and storage technologies (FAST)

作者： Kumar, Harendra Patel, Yuvraj Kesavan, Ram Makam, Sumith NetApp Madison WI USA Univ Wisconsin Madison Madison WI USA

ISBN: (纸本)9781931971362

We introduce a low-cost incremental checksum technique that protects metadata blocks against in-memory scribbles, and a lightweight digest-based transaction auditing mechanism that enforces file system consistency invariants. Compared with previous work, our techniques reduce performance overhead by an order of magnitude. they also help distinguish scribbles from logic bugs. We also present a mechanism to pinpoint the cause of scribbles on production systems. Our techniques have been productized in the NetApp (R) WAFL (R) (Write Anywhere file Layout) file system with negligible performance overhead, greatly reducing corruption-related incidents over the past five years, based on millions of run-time hours.

关键词： Metadata

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GearDB: a GC-free key-value store on HM-SMR drives with gear compaction 19

GearDB: a GC-free key-value store on HM-SMR drives with gear...

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proceedings of the 17th usenix conference on file and storage technologies

作者： Ting Yao Jiguang Wan Ping Huang Yiwen Zhang Zhiwen Liu Changsheng Xie Xubin He WNLO School of Computer Science and Technology Huazhong University of Science and Technology China and Key Laboratory of Information Storage System Ministry of Education of China and Temple University WNLO School of Computer Science and Technology Huazhong University of Science and Technology China and Key Laboratory of Information Storage System Ministry of Education of China Temple University

ISBN: (纸本)9781931971485

Host-managed shingled magnetic recording drives (HMSMR) give a capacity advantage to harness the explosive growth of data. Applications where data is sequentially written and randomly read, such as key-value stores based on Log-Structured Merge Trees (LSM-trees), make the HMSMR an ideal solution due to its capacity, predictable performance, and economical cost. However, building an LSM-tree based KV store on HM-SMR drives presents severe challenges in maintaining the performance and space efficiency due to the redundant cleaning processes for applications and storage devices (i.e., compaction and garbage collections). To eliminate the overhead of on-disk garbage collections (GC) and improve compaction efficiency, this paper presents GearDB, a GC-free KV store tailored for HM-SMR drives. GearDB proposes three new techniques: a new on-disk data layout, compaction windows, and a novel gear compaction algorithm. We implement and evaluate GearDB with LevelDB on a real HM-SMR drive. Our extensive experiments have shown that GearDB achieves both good performance and space efficiency, i.e., on average 1:71× faster than LevelDB in random write with a space efficiency of 89.9%.

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Tiny-Tail Flash: Near-Perfect Elimination of Garbage Collection Tail Latencies in NAND SSDs 15

Tiny-Tail Flash: Near-Perfect Elimination of Garbage Collect...

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15th usenix conference on file and storage technologies (FAST)

作者： Yan, Shiqin Li, Huaicheng Hao, Mingzhe Tong, Michael Hao Sundararaman, Swaminatahan Chien, Andrew A. Gunawi, Haryadi S. Univ Chicago Chicago IL 60637 USA Parallel Machines Tel Aviv Israel

ISBN: (纸本)9781931971362

TTFLASH is a "tiny-tail" flash drive (SSD) that eliminates GC-induced tail latencies by circumventing GC-blocked I/Os with four novel strategies: plane-blocking GC, rotating GC, GC-tolerant read, and GC-tolerant flush. It is built on three SSD internal advancements: powerful controllers, parity-based RAIN, and capacitor-backed RAM, but is dependent on the use of intra-plane copyback operations. We show that TTFLASH comes significantly close to a "no-GC" scenario. Specifically, between 99-99.99th percentiles, TTFLASH is only 1.0 to 2.6x slower than the no-GC case, while a base approach suffers from 5-138x GC-induced slowdowns.

关键词： Random access storage

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HopsFS: Scaling Hierarchical file System Metadata Using NewSQL Databases 15

HopsFS: Scaling Hierarchical File System Metadata Using NewS...

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15th usenix conference on file and storage technologies (FAST)

作者： Niazi, Salman Ismail, Mahmoud Haridi, Seif Dowling, Jim Grohsschmiedt, Steffen Ronstrom, Mikael KTH Royal Inst Technol Stockholm Sweden Spotify AB Stockholm Sweden Oracle Redwood City CA USA

ISBN: (纸本)9781931971362

Recent improvements in both the performance and scalability of shared-nothing, transactional, in-memory NewSQL databases have reopened the research question of whether distributed metadata for hierarchical file systems can be managed using commodity databases. In this paper, we introduce HopsFS, a next generation distribution of the Hadoop Distributed file System (HDFS) that replaces HDFS' single node in-memory metadata service, with a distributed metadata service built on a NewSQL database. By removing the metadata bottleneck, HopsFS enables an order of magnitude larger and higher throughput clusters compared to HDFS. Metadata capacity has been increased to at least 37 times HDFS' capacity, and in experiments based on a workload trace from Spotify, we show that HopsFS supports 16 to 37 times the throughput of Apache HDFS. HopsFS also has lower latency for many concurrent clients, and no downtime during failover. Finally, as metadata is now stored in a commodity database, it can be safely extended and easily exported to external systems for online analysis and free-text search.

关键词： Metadata

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