Publication | Closed Access
Dynamic Hub Labeling for Road Networks
45
Citations
23
References
2021
Year
Unknown Venue
Cluster ComputingTransport Network AnalysisEngineeringBig Data IndexingNetwork AnalysisHub LabelingDynamic NetworkIntelligent Traffic ManagementInformation RetrievalData ScienceCombinatorial OptimizationDynamic Hub LabelingIndex MaintenanceComputer ScienceGraph AlgorithmShortest Path FindingQuery OptimizationData IndexingNetwork ScienceGraph TheoryIndexing Technique
Shortest path finding is the building block of various applications in road networks and the index-based algorithms, especially hub labeling, can boost the query performance dramatically. However, the traffic condition keeps changing in real life, making the pre-computed index unable to answer the query correctly. In this work, we adopt the state-of-the-art tree decomposition-based hub labeling as the underlying index, and design efficient algorithms to incrementally maintain the index. Specifically, we first analyze the structural stability of the index in dynamic road networks which enables us to concentrate on label value maintenance. We then introduce the minimum weight property and minimum distance property to guarantee the index correctness without graph traversal. Moreover, we propose the star-centric paradigm for tracing index change and design various pruning techniques to further accelerate the index maintenance. Finally, we extend our algorithms to batch mode for shared computation, extend to structural maintenance for full types of update, and generalize to all kinds of TDHL. Our experimental results validate the superiority of our proposals over existing solutions on both index maintenance and query processing.
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