Go to DBLP homepageDHL: an efficient hierarchical index for shortest distance querying in time-dependent road networks
Abstract: A shortest distance query is a fundamental operation of various location-based services in time-dependent road networks. Unfortunately, existing methods (e.g., G-tree-like, 2-hop labeling-like) are prohibitively expensive in terms of space/time. To this end, we propose a novel Double Hierarchical Labeling (DHL) index, which consists of a Hierarchical Graph Partition (HGP) tree and a hierarchical border labeling list. For HGP-tree, we first use a hierarchical graph partitioning to split the entire road network into hierarchical subgraphs and then index these subgraphs by a balanced tree. To preserve all connectivity information between border vertices of subgraphs, a Time-based Distance Inverted File (TDIF) is constructed for each leaf node of the HGP-tree. For the hierarchical labeling list, we construct it only for border vertices and use it to sped-up query processing. Moreover, a label propagation update is proposed to manage label updating when weights change. Considering three different situations between the given query vertices, we propose a phase-aware search algorithm with an extra-pruning method. Meanwhile, we extend our query methods to support the latest departure time querying. At last, to further improve the query efficiency and guarantee the algorithm can handle very large time-dependent road networks, we obtain the global boundaries and develop an efficient intra-pruning algorithm OPGB which does not rely on any additional parameter. We conduct extensive experiments on eight real-world datasets. As shown in the results, by adopting different pruning technologies, our proposed DHL achieves 44.09% and 54.83% speedup on average for the distance querying when compared with the state-of-the-art methods respectively which demonstrate the superiority of the proposed proposals on query processing and index maintenance.
External IDs:dblp:journals/vldb/DanPZM25
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