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HGeoHashBase: an optimized storage model of spatial objects for location-based services

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Abstract

Many location-based services need to query objects existing in a specific space, such as location-based tourism resource recommendation. Both a large number of spatial objects and the real-time object access requirements of location-based services pose a big challenge for spatial object storage and query management. In this paper, we propose HGeoHashBase, an improved storage model by integrating GeoHash with key-value structure, to organize spatial objects for efficient range queries. GeoHash is responsible for spatial encoding and key-value structure as underlying data storage. Both the similarity of the encodings for objects in the close geographical locations and the multi-version data mechanism are blended into the proposed model well. Considering the tradeoff between encoding precision and query performance, a theoretical proof is presented. Extensive experiments are designed and conducted, whose results show that the proposed model can gain significant performance improvement.

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Acknowledgements

This study is supported by the National Natural Science Foundation of China (Grant Nos. 61462017, 61363005, U1501252, 61662013), Guangxi Natural Science Foundation of China (2017GXNSFAA198035, 2014GXNSFAA118353, 2014GXNSFAA118390), Guangxi Key Laboratory of Automatic Detection Technology and Instrument Foundation (YQ15110), Guangxi Cooperative Innovation Center of Cloud Computing and Big Data, and the High Level Innovation Team of Colleges and Universities in Guangxi and Outstanding Scholars Program Funding.

Author information

Authors and Affiliations

  1. Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin, 541004, China

    Jingwei Zhang, Chao Yang & Yuming Lin

  2. Guangxi Cooperative Innovation Center of Cloud Computing and Big Data, Guilin University of Electronic Technology, Guilin, 541004, China

    Jingwei Zhang & Chao Yang

  3. Guangxi Key Laboratory of Automatic Measurement Technology and Instrument, Guilin University of Electronic Technology, Guilin, 541004, China

    Qing Yang

  4. Centre for Applied Informatics, College of Engineering and Science, Victoria University, Melbourne, 8001, Australia

    Yanchun Zhang

Authors
  1. Jingwei Zhang
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  2. Chao Yang
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  3. Qing Yang
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  4. Yuming Lin
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  5. Yanchun Zhang
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Corresponding author

Correspondence to Qing Yang.

Additional information

Jingwei Zhang is an associate professor at School of Computer and Information Security, Guilin University of Electronic Technology, China. He obtained his PhD from East China Normal University, China in 2012. His research interests include massive data management, distributed computing framework, Web data analysis and big data analytics for emerging applications.

Chao Yang has obtained the master degree from Guilin University of Electronic Technology, China. His research interests include large-scale data computation optimization and big data services for smart tourism.

Qing Yang is an associate professor at School of Electronics Engineering and Automation, Guilin University of Electronic Technology, China. Her research interests include intelligent information processing, social network analysis, and large-scale data processing optimization.

Yuming Lin is an associate professor at School of Computer and Information Security, Guilin University of Electronic Technology, China. He obtained his PhD from East China Normal University, China in 2013. His research interests include sentiment analysis, Web data mining and knowledge graph.

Yanchun Zhang is a professor and the director of the Centre for Applied Informatics, Victoria University, Australia. He received his PhD degree from the University of Queensland, Australia in 1991. He is the Editor-In-Chief of World Wide Web journal (Springer), and Health Information Science and Systems (BioMed Central). He is the Chairman of the International Web Information Systems Engineering Society (WISE Society). He was a member of ARC College of Experts from 2008 to 2010. He received the National “Thousand Talent Program” Award from China in 2010. His research interests include big data analytics, eHealth, Social networking, and Web services.

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Zhang, J., Yang, C., Yang, Q. et al. HGeoHashBase: an optimized storage model of spatial objects for location-based services. Front. Comput. Sci. 14, 208–218 (2020). https://doi.org/10.1007/s11704-018-7030-3

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  • DOI: https://doi.org/10.1007/s11704-018-7030-3

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