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Probabilistic nearest neighbor query processing on distributed uncertain data

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Abstract

A nearest neighbor (NN) query, which returns the most similar object to a user-specified query object, plays an important role in a wide range of applications and hence has received considerable attention. In many such applications, e.g., sensor data collection and location-based services, objects are inherently uncertain. Furthermore, due to the ever increasing generation of massive datasets, the importance of distributed databases, which deal with such data objects, has been growing. One emerging challenge is to efficiently process probabilistic NN queries over distributed uncertain databases. The straightforward approach, that each local site forwards its own database to the central server, is communication-expensive, so we have to minimize communication cost for the NN object retrieval. In this paper, we focus on two important queries, namely top-k probable NN queries and probabilistic star queries, and propose efficient algorithms to process them over distributed uncertain databases. Extensive experiments on both real and synthetic data have demonstrated that our algorithms significantly reduce communication cost.

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Notes

  1. http://mkt.unwto.org.

  2. As long as a distance can be computed, our algorithms function, hence we can apply any distance metrics.

  3. http://www.chorochronos.org/.

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Acknowledgments

This research is partially supported by the Grant-in-Aid for Scientific Research (A) (26240013) of MEXT, Japan, and JST, Strategic International Collaborative Research Program, SICORP.

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Authors and Affiliations

  1. Department of Multimedia Engineering Graduate School of Information Science and Technology Osaka University, 1-5 Yamadaoka, Suita, Osaka, 565-0871, Japan

    Daichi Amagata, Takahiro Hara & Shojiro Nishio

  2. Department of Systems and Social Informatics, Graduate School of Information Science Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan

    Yuya Sasaki

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  1. Daichi Amagata
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  2. Yuya Sasaki
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Correspondence to Daichi Amagata.

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Amagata, D., Sasaki, Y., Hara, T. et al. Probabilistic nearest neighbor query processing on distributed uncertain data. Distrib Parallel Databases 34, 259–287 (2016). https://doi.org/10.1007/s10619-015-7183-0

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