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SCG-tree: shortcut enhanced graph hierarchy tree for efficient spatial queries on massive road networks

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Abstract

Nowadays, location-based services are widely used, requiring instant responses to a large volume of multiple spatial queries over massive road networks, i.e., single-pair shortest path (SPSP) query, k-nearest neighbor (kNN) query, and range query. Creating index-based structure for each kind of query is costly, hence it is important to handle multiple spatial queries within one efficient structure. Partition-based hierarchical approaches show promising potential to meet the requirement. However, existing approaches require large search space on massive road networks especially for long-distance queries, which is inefficient and hard to scale. To overcome the drawbacks, we propose the shortcut-enhanced graph hierarchy tree (SCG-tree), which leverages shortcuts to effectively prune the search space over a hierarchical structure. With the SCG-tree, a pruned shortcut-based method is designed to answer SPSP query, and a two-phase expansion strategy is proposed to leverage shortcuts for kNN and range queries. Theoretical analyses show the superiority of proposed shortcut-based query algorithms. Extensive experiments demonstrate that our approach can achieve three times speedup for kNN query and an order of magnitude speedup for SPSP and range queries over existing methods on real road networks that scale up to 24 million nodes and 58 million edges.

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Acknowledgements

We thank the anonymous reviewers for their valuable feedback. This research was supported by the Frontier Technology R&D Project of Jiangsu (BF2024059), the National Natural Science Foundation of China (Grant No. 6240071854), the Natural Science Foundation of Jiangsu Province (BK20241381), the Jiangsu Association for Science and Technology Youth Science and Technology Talent Support Project (JSTJ-2023-XH055).

Author information

Authors and Affiliations

  1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210023, China

    Zhuo Cao, Chun Cao, Jingwei Xu, Zhefei Chen & Xiaoxing Ma

  2. Software Institute, Nanjing University, Nanjing, 210093, China

    Zhuo Cao & Xiaoxing Ma

  3. School of Computer Science and Technology, Nanjing University, Nanjing, 210023, China

    Chun Cao, Jingwei Xu, Zhefei Chen & Xiaoxing Ma

  4. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Jianqiu Xu & Zi Chen

Authors
  1. Zhuo Cao
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Correspondence to Chun Cao.

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Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

Additional information

Zhuo Cao received the MS degree in mechanical electronics engineering from Guizhou University, China in 2020. He is currently pursuing a PhD degree in software engineering at Nanjing University, China. His main research interests include spatio-temporal data management and model-driven engineering.

Chun Cao received the PhD degree from Nanjing University, Nanjing, China, in 2007. He is currently a professor in School of Computer Science and Technology at the Nanjing University, China. His research interests include software engineering and Internetware.

Jianqiu Xu is currently a professor with the Nanjing University of Aeronautics and Astronautics, China. His research interests include spatial databases and moving objects databases, and has published over 50 journal and confernece papers such as TKDE, ICDE, PVLDB Geoinformatica and MDM. He is on the program committees for conferences, including the PVLDB, ICDE, KDD, DASFAA, and MDM.

Jingwei Xu is currently an assistant professor in the School of Computer Science at Nanjing University, China. His research primarily focuses on the engineering aspects of intelligent software. In recent years, he has concentrated on intelligent software DevOps, software testing of intelligent modules, reliability, and quality assurance. He has also conducted in-depth research on Large Langunage Models. His work has been published in top international conferences and journals in software engineering (FSE, ICSE, ASE) and in machine learning and data mining (NeurIPS, ICLR, KDD, IJCAI, TKDE). He also serves as a program committee member for international conferences including ICML, NeurIPS, ICLR, KDD, WWW, SIGIR, and AAAI.

Zhefei Chen received his BS degree in computer science and technology from Nanjing University, China in 2020. He is currently pursuing a Master degree in computer science at Nanjing University, China. His research interests include domain specific language and model-driven engineering.

Zi Chen received the PhD degree in the Software Engineering Institute, East China Normal University, China in 2021. She is currently an associate professor in Nanjing University of Aeronautics and Astronautics, China. Her research interest is big graph data query and analysis, including cohesive subgraph search on large-scale social networks and path planning on road networks. She has published papers in VLDB, ICDE, TKDE, and WWW.

Xiaoxing Ma received the PhD degree from Nanjing University, China in 2003. He is currently a professor in School of Computer Science and Technology at the Nanjing University, China. His research interests include adaptive software systems, software architectures and middleware systems, and assurance of software qualities.

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Cao, Z., Cao, C., Xu, J. et al. SCG-tree: shortcut enhanced graph hierarchy tree for efficient spatial queries on massive road networks. Front. Comput. Sci. 19, 199610 (2025). https://doi.org/10.1007/s11704-024-40459-x

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