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An efficient location reporting and indexing framework for urban road moving objects

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Abstract

The tracking of moving objects consists of two critical operations: location reporting, in which moving objects (or clients) send their locations to centralized servers, and index maintenance, through which centralized servers update the locations of moving objects. In existing location reporting techniques, each moving object reports its locations to servers by utilizing long-distance links such as 3G/4G. Corresponding to this location reporting strategy, servers need to respond to all the location updating requests from individual moving objects. Such techniques suffer from very high communication cost (due to the individual reporting using long-distance links) and high index update I/Os (due to the massive amount of location updating requests). In this paper, we present a novel Group-movement based location Reporting and Indexing (GRI) framework for location reporting (at moving object side) and index maintenance (at server side). In the GRI framework, we introduce a novel location reporting strategy which allows moving objects to report their locations to servers in a group (instead of individually) by aggregating the moving objects that share similar movement patterns through wireless local links (such as WiFi). At the server side, we present a dual-index, Hash-GTPR-tree (H-GTPR), to index objects sharing similar movement patterns. Our experimental results on synthetic and real data sets demonstrate the effectiveness and efficiency of our new GRI framework, as well as the location reporting strategy and the H-GTPR tree index technique.

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Notes

  1. http://www.openstreetmap.org/.

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Acknowledgements

We sincerely thank Professor Alexandra Poulovassilis from London Knowledge Lab (LKL) for her valuable suggestions to our work, Yu Lu for her assistance in preparing data for the experiments, and the anonymous reviewers for their valuable comments.

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210003, P.R. China

    Jingyu Han & Kejia Chen

  2. Institute of Software, Chinese Academy of Science, Beijing, 100080, P.R. China

    Zhiming Ding

  3. Department of Computer Science, New Mexico State University, Las Cruces, USA

    Huiping Cao

Authors
  1. Jingyu Han
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  2. Kejia Chen
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  3. Zhiming Ding
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  4. Huiping Cao
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Corresponding author

Correspondence to Jingyu Han.

Additional information

Communicated by Divyakant Agrawal.

This research is partially supported by National Natural Science Foundation of China under the grant numbers 61003040, 91124001, 61100135, and China 973 program 2011CB302903.

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Han, J., Chen, K., Ding, Z. et al. An efficient location reporting and indexing framework for urban road moving objects. Distrib Parallel Databases 32, 271–311 (2014). https://doi.org/10.1007/s10619-013-7135-5

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