Using provenance to efficiently improve metadata searching performance in storage systems

Liu, Jinjun; Feng, Dan; Hua, Yu; Peng, Bin; Nie, Zhenhua

doi:10.1016/j.future.2014.10.030

Cited by 13 publications

(3 citation statements)

References 17 publications

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“….55 of weighted average score, but they seemed ignored to intuitive navigation as weighted average score was in 3.79. However, this feature supports the classical database and organization of knowledge as well as improve metadata searching performance [20], [21]. Besides, this feature also is an academic portfolio in the digitalization era [22].…”

Section: Resultsmentioning

confidence: 99%

Taking Mendeley as Multimedia-based Application in Academic Writing

Patak¹,

Naim²,

Park³

2016

International Journal on Advanced Science, Engineering and Information Technology

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Mendeley is one of the references managers that provide web, desktop, and mobile version. This research aims at exploring the Indonesian Mendely users' preference on Mendeley use as multimedia-based application in academic writing. The researchers conducted survey research design to find data for deciding the obvious groups' characteristics on certain topic or issue in a diverse group. Data on this research was taken in 2015 to explore 100 Indonesian Mendeley users' preference on Mendeley features as web based application in academic writing. The researchers used weighted average find out rate and percentage adjusment for the influence of a binary confounder. The weighted average in this research was automatically generated by SurveyMonkey analytic. This research indicated what Mendeley features as multimedia web application for academic writing that Indonesian Mendeley users took in and out.

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Section: Resultsmentioning

confidence: 99%

Taking Mendeley as Multimedia-based Application in Academic Writing

Patak¹,

Naim²,

Park³

2016

International Journal on Advanced Science, Engineering and Information Technology

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“…Rapport [20] build files' namespace by utilizing their semantic correlation and exploiting dynamic evolution of attributes to support namespace management and complex queries. PROMES [34] is a relationship graph-based searching method. It will be efficient in the small-scale file system, because it needs to analyse the provenance's information that will extend the latency of searching, and maintain the relationship graph consistent with metadata updated that will degrade the performance further.…”

Section: Metadata Search Based On Semanticsmentioning

confidence: 99%

MBFS: a parallel metadata search method based on Bloomfilters using MapReduce for large-scale file systems

et al. 2015

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The metadata search is an important way to access and manage file systems. Many solutions have been proposed to tackle performance issue of metadata search. However, the existing solutions build a separate metadata index at the internal or external file system through the related data structure or database use semantics and event-notification method to construct the index structure, utilize the sampling-based method to conduct direct metadata search on the namespace, face problems of the high I/O overhead for maintaining consistency between metadata indexes and metadata, have enormous space overhead for metadata indexes storing and low accuracy of results and so on. To address these problems, this paper presents MBFS, a fast, accurate and lightweight metadata search method based on multi-dimensional Bloomfilters. We create a multi-dimensional Bloomfilter structure on the basis of the directory entry that can prune sub-trees to narrow the search scope of namespace. MBFS is capable of producing fast and accurate answers for a class of complex search over a file system after consuming a small number of disk accesses. MBFS residing in the file system B Zhisheng Huo 123 Z. Huo et al.does not need additional I/O overhead to maintain consistency. MBFS consists of Bloomfilters which are composed of bits, so it is a lightweight metadata search method that consumes marginal space overhead. Moreover, MBFS employs MapReduce for speeding up search under the environment of multiple metadata servers. Extensive experiments are conducted to prove the effectiveness of MBFS. The experimental results show that MBFS can achieve an excellent performance not only on the search latency, but also on the accuracy of results with low space and time overhead.

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“…In the first paper Liu et al [9] state that metadata search performance has become increasingly important but index trees cannot offer better performance due to the hierarchical indexing bottleneck. They propose a novel provenance based metadata search system.…”

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confidence: 99%