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SMashQ: spatial mashup framework for k-NN queries in time-dependent road networks

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Abstract

The k-nearest-neighbor (k-NN) query is one of the most popular spatial query types for location-based services (LBS). In this paper, we focus on k-NN queries in time-dependent road networks, where the travel time between two locations may vary significantly at different time of the day. In practice, it is costly for a LBS provider to collect real-time traffic data from vehicles or roadside sensors to compute the best route from a user to a spatial object of interest in terms of the travel time. Thus, we design SMashQ, a server-side spatial mashup framework that enables a database server to efficiently evaluate k-NN queries using the route information and travel time accessed from an external Web mapping service, e.g., Microsoft Bing Maps. Due to the expensive cost and limitations of retrieving such external information, we propose three shared execution optimizations for SMashQ, namely, object grouping, direction sharing, and user grouping, to reduce the number of external Web mapping requests and provide highly accurate query answers. We evaluate SMashQ using Microsoft Bing Maps, a real road network, real data sets, and a synthetic data set. Experimental results show that SMashQ is efficient and capable of producing highly accurate query answers.

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Authors and Affiliations

  1. Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China

    Detian Zhang & Xinming Zhang

  2. Department of Computer Science, City University of Hong Kong, Hong Kong, China

    Detian Zhang, Chi-Yin Chow & Qing Li

  3. USTC-CityU Joint Advanced Research Center, Suzhou, China

    Detian Zhang, Qing Li & Xinming Zhang

Authors
  1. Detian Zhang
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  2. Chi-Yin Chow
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  3. Qing Li
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  4. Xinming Zhang
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  5. Yinlong Xu
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Corresponding author

Correspondence to Chi-Yin Chow.

Additional information

The work described in this paper was partially supported by grants from City University of Hong Kong (Project No. 7002686 and 7002606) and the National Natural Science Foundation of China under Grant No. 61073185 and 61073038.

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Zhang, D., Chow, CY., Li, Q. et al. SMashQ: spatial mashup framework for k-NN queries in time-dependent road networks. Distrib Parallel Databases 31, 259–287 (2013). https://doi.org/10.1007/s10619-012-7110-6

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  • DOI: https://doi.org/10.1007/s10619-012-7110-6

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