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Indexing spatial data in cloud data managements
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DOI：10.1016/j.pmcj.2013.07.001.png)
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摘要
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With the proliferation of smart phones and location-based services, the amount of data with spatial information, referred to as spatial data, is dramatically increasing. Cloud computing plays an important role handling large-scale data analysis, and several cloud data managements (CDMs) have been developed for processing data. CDMs usually provide key-value storage, where each key is used to access its corresponding value. However, user-generated spatial data are usually distributed non-uniformly. In this paper, we present a novel key design based on an R+-tree (KR+-index) for retrieving skewed spatial data efficiently. In the experiments, we implement the KR+-index on Cassandra, and study its performance using spatial data. Experiments show that the KR+-index outperforms the-state-of-the-art methods. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Cloud data management
Geographic data
Spatial index
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3.5
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