Logan:自动管理可进化的、大规模的档案存储

M. Storer, K. Greenan, I. Adams, E. L. Miller, D. Long, K. Voruganti
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引用次数: 6

摘要

用于保存科学数据、商业数据和消费者数据的归档存储系统必须在数十年内维护和保护数万个介质上的数十到数百pb的数据。目前,此类系统的设计方式与高性能、短期存储系统相同,后者具有使用寿命,但必须通过ldquofork-liftrdquo升级来全部替换。因此,虽然现有的解决方案可以提供良好的能源效率和相对较低的成本,但它们不能很好地适应技术的不断改进,随着年龄的增长,相对于当前的技术,它们的效率会降低。在归档存储环境中,此范例意味着一系列的大规模迁移和升级,以保持效率和最新。我们的方法,Logan,管理智能存储设备分布式网络上的节点添加、删除和故障,允许系统随着设备技术的进步而逐渐发展。通过自动处理大多数常见的管理工作(将新设备集成到系统中、管理一起工作以提供冗余的设备组以及从故障设备中恢复),logan减少了管理开销,从而降低了成本。Logan还可以通过识别和淘汰过时的设备来提高成本和空间效率,从而减少档案存储系统的空间和电力需求。
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Logan: Automatic management for evolvable, large-scale, archival storage
Archival storage systems designed to preserve scientific data, business data, and consumer data must maintain and safeguard tens to hundreds of petabytes of data on tens of thousands of media for decades. Such systems are currently designed in the same way as higher-performance, shorter-term storage systems, which have a useful lifetime but must be replaced in their entirety via a ldquofork-liftrdquo upgrade. Thus, while existing solutions can provide good energy efficiency and relatively low cost, they do not adapt well to continuous improvements in technology, becoming less efficient relative to current technology as they age. In an archival storage environment, this paradigm implies an endless series of wholesale migrations and upgrades to remain efficient and up to date. Our approach, Logan, manages node addition, removal, and failure on a distributed network of intelligent storage appliances, allowing the system to gradually evolve as device technology advances. By automatically handling most of the common administration chores-integrating new devices into the system, managing groups of devices that work together to provide redundancy, and recovering from failed devices-Logan reduces management overhead and thus cost. Logan can also improve cost and space efficiency by identifying and decommissioning outdated devices, thus reducing space and power requirements for the archival storage system.
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Performance of RDMA-capable storage protocols on wide-area network Just-in-time staging of large input data for supercomputing jobs Introducing map-reduce to high end computing Scalable full-text search for petascale file systems Logan: Automatic management for evolvable, large-scale, archival storage
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