Making the best of a bad situation: Prioritized storage management in GEMS

Wozniak, Justin M.; Thain, Douglas; Striegel, Aaron; Izaguirre, Jesús A.

doi:10.1016/j.future.2007.04.003

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…GEMS also manages access control lists in the volunteered space, and provides an authentication mechanism [11] compatible with existing techniques. Observed deviations from system policy are prioritized and repaired [4,13] without user intervention, by locating, allocating, and using additional available disk space in accordance with user policy. A diagram of example operation is shown in Fig.3.2.…”

Section: Gems Architecturementioning

confidence: 99%

GEMS: User Control for Cooperative Scientific Repositories

Wozniak

Chatterjee

Thain

et al. 2011

Computer Communications and Networks

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Data repositories are an integral part of modern scientific computing systems. While a variety of grid-enabled storage systems have been developed to improve scalability, administrative control, and interoperability, users have several outstanding needs: to seamlessly and efficiently work with replicated data sets, to customize system behavior within a grid, and to quickly tie together remotely administered grids or independently operated resources. This is particularly true in the small virtual organization, in which a subset of possible users seek to coordinate subcomponents of existing grids into a workable collaborative system. Our approach to this problem starts with the storage system and seeks to enable this functionality by creating ad hoc storage grids. Modern commodity hardware in use at research labs and university networks ships with an abundance of storage space that is often underutilized, and even consumer gadgets provide extensive storage resources that will not immediately be filled. The installation of simple software enables these systems to be pooled and cataloged into a spacious, parallel ad hoc storage network. While traditional storage networks or tertiary storage systems are isolated behind file servers and firewalls, constricting data movement, we layer the storage service network atop the client consumer network, improving the available network parallelism and boosting I/O performance for data-intensive scientific tasks.

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Section: Gems Architecturementioning

confidence: 99%

GEMS: User Control for Cooperative Scientific Repositories

Wozniak

Chatterjee

Thain

et al. 2011

Computer Communications and Networks

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QoS-based storage resources provisioning for grid applications

Skałkowski

Słota

Król

et al. 2013

Future Generation Computer Systems

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Overdrive Controllers for Distributed Scientific Computation

Wozniak

2007

Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)

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Large distributed computer systems have been successfully employed to solve modern scientific problems that were previously impracticable. Tools exist to bind together notably underutilized high speed computers and sizable storage resources, creating architectures that provide performance and capacity that scales with the quantity of resources invested. In various forms such as Internet computing, desktop grids, and even "big iron" grids, users and administrators find it difficult, however, to obtain aggregate systems that are more reliable than their underlying components and simple to utilize in concert. In this work, we will propose a model for controlling complex distributed systems and its application to the construction of scientific repositories.

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Making the best of a bad situation: Prioritized storage management in GEMS

Cited by 3 publications

References 25 publications

GEMS: User Control for Cooperative Scientific Repositories

GEMS: User Control for Cooperative Scientific Repositories

QoS-based storage resources provisioning for grid applications

Overdrive Controllers for Distributed Scientific Computation

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