An Adaptive Synchronization Policy for Harvesting OAI-PMH Repositories

N. Adly
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引用次数: 1

Abstract

Metadata harvesting requires timely propagation of up-to-date information from thousands of Repositories over a wide area network. It is desirable to keep the data as fresh as possible while observing the overhead on the Harvester. An important dimension to be considered is that Repositories vary widely in their update patterns; they may experience different update rates at different times or unexpected changes to update patterns. In this paper, we define data Freshness metrics and propose an adaptive algorithm for the synchronization of the Harvester with the Repositories. The algorithm is based on meeting a desired level of Freshness while incurring the minimum overhead on the Harvester. We present a comparison between different policies for the synchronization within the framework devised. It is shown that the proposed policy outperform the other policies, especially for heterogeneous update patterns.
用于获取OAI-PMH存储库的自适应同步策略
元数据收集需要在广域网上及时传播来自数千个存储库的最新信息。在观察收割机上的开销时,尽可能保持数据的新鲜是可取的。需要考虑的一个重要方面是,存储库的更新模式差异很大;它们可能在不同的时间经历不同的更新速率或更新模式的意外更改。在本文中,我们定义了数据新鲜度指标,并提出了一种自适应算法,用于采集器与存储库的同步。该算法是基于满足所需的新鲜度水平,同时在收割机上产生最小的开销。我们在所设计的框架内对不同的同步策略进行了比较。结果表明,该策略优于其他策略,特别是对于异构更新模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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