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Speeding Up Reachability Queries in Public Transport Networks Using Graph Partitioning
Information Systems Frontiers ( IF 5.9 ) Pub Date : 2021-08-14 , DOI: 10.1007/s10796-021-10164-2
Bezaye Tesfaye 1 , Nikolaus Augsten 1 , Mateusz Pawlik 1 , Michael H Böhlen 2 , Christian S Jensen 3
Affiliation  

Computing path queries such as the shortest path in public transport networks is challenging because the path costs between nodes change over time. A reachability query from a node at a given start time on such a network retrieves all points of interest (POIs) that are reachable within a given cost budget. Reachability queries are essential building blocks in many applications, for example, group recommendations, ranking spatial queries, or geomarketing. We propose an efficient solution for reachability queries in public transport networks. Currently, there are two options to solve reachability queries. (1) Execute a modified version of Dijkstra’s algorithm that supports time-dependent edge traversal costs; this solution is slow since it must expand edge by edge and does not use an index. (2) Issue a separate path query for each single POI, i.e., a single reachability query requires answering many path queries. None of these solutions scales to large networks with many POIs. We propose a novel and lightweight reachability index. The key idea is to partition the network into cells. Then, in contrast to other approaches, we expand the network cell by cell. Empirical evaluations on synthetic and real-world networks confirm the efficiency and the effectiveness of our index-based reachability query solution.



中文翻译:

使用图分区加速公共交通网络中的可达性查询

计算公共交通网络中的最短路径等路径查询具有挑战性,因为节点之间的路径成本会随着时间而变化。在这样的网络上,在给定开始时间来自节点的可达性查询检索在给定成本预算内可达的所有兴趣点 (POI)。可达性查询是许多应用程序中必不可少的构建块,例如组推荐、空间排名查询或地理营销。我们为公共交通网络中的可达性查询提出了一种有效的解决方案。目前,有两种方法可以解决可达性查询。(1) 执行支持时间相关边遍历成本的 Dijkstra 算法的修改版本;这个解决方案很慢,因为它必须逐边扩展并且不使用索引。(2) 对每个单独的 POI 发出单独的路径查询,即 单个可达性查询需要回答许多路径查询。这些解决方案都不能扩展到具有许多 POI 的大型网络。我们提出了一种新颖且轻量级的可达性指数。关键思想是将网络划分为单元。然后,与其他方法相比,我们逐个单元地扩展网络。对合成网络和真实网络的实证评估证实了我们基于索引的可达性查询解决方案的效率和有效性。

更新日期:2021-08-19
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