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arXiv 0810.2227cs.DC
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海量数据的分布式管理:一种高效的细粒度数据访问方案

Distributed Management of Massive Data: an Efficient Fine-Grain Data Access Scheme

Bogdan Nicolae, Gabriel Antoniu, Luc Bougé

摘要:

针对大规模分布式环境下海量数据块的高效存储和访问问题,提出了一种基于数据块的数据子集细粒度访问方法。这个问题在数据库、数据采掘和多媒体领域的应用中至关重要。我们提出了一个数据共享服务的基础上分布式,基于RAM的数据存储,同时利用基于DHT的,原生并行元数据管理方案。相对于最常用的网格存储基础设施,提供明确的数据本地化和传输机制,我们提供了一个透明的访问模型,通过全局标识符访问数据。我们的建议已通过原型实施,其初步评估提供了有前途的结果进行了验证。

英文摘要:

This paper addresses the problem of efficiently storing and accessing massive data blocks in a large-scale distributed environment, while providing efficient fine-grain access to data subsets. This issue is crucial in the context of applications in the field of databases, data mining and multimedia. We propose a data sharing service based on distributed, RAM-based storage of data, while leveraging a DHT-based, natively parallel metadata management scheme. As opposed to the most commonly used grid storage infrastructures that provide mechanisms for explicit data localization and transfer, we provide a transparent access model, where data are accessed through global identifiers. Our proposal has been validated through a prototype implementation whose preliminary evaluation provides promising results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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