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Searchable Storage in Cloud Computing pp 1–22Cite as

Backgrounds of Searchable Storage

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Abstract

Multi-dimensional data indexing has received much research attention recently in a centralized system. However, it remains a nascent area of research in providing an integrated structure for multiple queries on multi-dimensional data in a distributed environment. We propose a new data structure, called BR-tree (Bloom filter based R-tree), and implement such a prototype in the context of a distributed system. The node in a BR-tree, viewed as an expansion from the traditional R-tree node structure, incorporates space-efficient Bloom filters to facilitate fast membership queries. The proposed BR-tree can simultaneously support not only existing point and range queries but also cover and bound queries that can potentially benefit various data indexing services. Compared with previous data structures, BR-tree achieves space efficiency and provides quick response (\(\le O(log~n)\)) on these four types of queries. Our extensive experiments in a distributed environment further validate the practicality and efficiency of the proposed BR-tree structure (©{2009}IEEE. Reprinted, with permission, from Ref. [1].).

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Authors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, Hubei, China

    Yu Hua

  2. McGill University, Montreal, QC, Canada

    Xue Liu

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  1. Yu Hua
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  2. Xue Liu
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Correspondence to Yu Hua .

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Hua, Y., Liu, X. (2019). Backgrounds of Searchable Storage. In: Searchable Storage in Cloud Computing. Springer, Singapore. https://doi.org/10.1007/978-981-13-2721-6_1

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  • DOI: https://doi.org/10.1007/978-981-13-2721-6_1

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  • Print ISBN: 978-981-13-2720-9

  • Online ISBN: 978-981-13-2721-6

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