Abstract
For location-based services (LBS), the path with the shortest travel time is much more meaningful than the one with the shortest network distance, as it considers the live traffics in road networks. Usually, there are two ways for an LBS provider to provide the shortest travel-time paths for its queries, i.e., computing by itself or retrieving from external Web mapping services. However, both of these two ways are expensive, like costly computation and long latency. To accelerate shortest path query processing, we design an effective cache of shortest travel-time paths for LBS providers in this paper. Unlike the conventional path caching techniques, where the caches are only suitable for distance-based paths, our proposed cache is dynamic and can support travel-time-based paths. More importantly, a new cache operation, namely path join, is devised to estimate the path information for a query based on the cached paths, when the cache can not answer the query directly. Experimental results on a real Web mapping service and datasets confirm the effectiveness of the proposed techniques.
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Notes
In the real world, a cache could be part of a server.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Project 61702227, Project 61472337, Project 61572336, Project 61602214, Project 61602137, and Project 61632016, in part by the Natural Science Foundation of Jiangsu Province under Project BK20160191, in part by the Natural Science Research Project of Jiangsu Higher Education Institution (No. 17KJA520003). The last author (Qing Li) has also been supported by a contract project from the South China University of Technology.
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This article belongs to the Topical Collection: Special Issue on Deep vs. Shallow: Learning for Emerging Web-scale Data Computing and Applications
Guest Editors: Jingkuan Song, Shuqiang Jiang, Elisa Ricci, and Zi Huang
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Zhang, D., Liu, A., Li, Z. et al. Effective shortest travel-time path caching and estimating for location-based services. World Wide Web 22, 455–475 (2019). https://doi.org/10.1007/s11280-018-0549-2
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DOI: https://doi.org/10.1007/s11280-018-0549-2