Customizable Route Planning in External Memory

نویسندگان

  • Janis Hamme
  • Dorothea Wagner
  • Peter Sanders
  • Julian Dibbelt
  • Moritz Baum
چکیده

Route planning is a popular application for mobile devices, but still some problems have not been solved for road networks of continental size. Major constraints are the limited resources, that do not allow entire road networks to be held in main memory. Only a fraction of the complete road network can be held in main memory at once – most of the data must reside in external memory. To allow efficient computation of shortest paths, the data must be arranged in a way that allows efficient access. Computed routes must be optimal for a specific metric, e.g., have an optimal distance or travel time. These metrics are likely to change frequently, e. g., as traffic data or driving preferences have to be considered. However, current approaches to mobile route planning, are based on metric-dependent preprocessing of data, that is too expensive for execution on mobile devices. Hence, they can not comply with real-world requirements, that include dynamic and user defined metrics. Customizable Route Planning [1, 2], is a speedup technique, that separates preprocessing in two stages. As a result of metric-independent graph partitioning in a first stage, fast metric customization is possible for arbitrary metrics afterwards. Based on the results of Customizable Route Planning, we develop a proof-of-concept application for mobile devices. It demonstrates, that metric customization of road networks in external memory is possible in a few minutes. Then, the precomputed data can be used to compute exact shortest paths. Zusammenfassung Straßennavigation auf mobilen Geräten ist eine beliebte Anwendung, dennoch sind noch nicht alle Probleme für Straßennetzwerke kontinentaler Größe gelöst. Hautprobleme sind die begrenzten Ressourcen mobiler Geräte, welche es nicht zulassen, dass komplette Straßennetzwerke in den Hauptspeicher geladen werden können. Zur Berechnung von Routen auf mobilen Systemen müssen daher Techniken anwendet werden, welche das Problem so unterteilen, dass nur wenige Teile der Daten gleichzeitig aus externem Speicher geladen werden. Berechneten Routen müssen bezüglich einer Metrik, z.B. hinsichtlich ihrer Länge oder Reisezeit, optimal sein. In der Realität sind Metriken vielfältig, da beispielsweise die aktuelle Verkehrssituation oder benutzerspeziefischen Fahrgewohnheiten berücksichtigt werden müssen. Aktuelle Lösungen zur Berechnung von optimalen Routen auf mobilen Geräten beruhen allerdings auf rechenintensiven, metrik-abhängigen Vorberechnungen, die nicht auf mobilen Geräten durchführbar sind. Sie können daher den realen Anforderungen, welche dynamische und benutzerdefinierte Metriken beinhalten, nicht gerecht werden. Customizable Route Planning [1, 2], ist eine Beschleunigungstechnik, welche die nötigen Vorberechnungen zweiteilt. Durch geschickte Partitionierung, können metrikabhängige Vorberechnungen in einem zweiten, wesentlich schnelleren Schritt erfolgen. Aufbauend auf den Ergebnissen von Customizable Route Planning zeigen wir, dass metrik-abhängige Vorberechnungen, durch das effiziente Nutzen von externem Speicher, auch auf mobilen Geräten in wenigen Minuten durchführbar sind. Die vorberechneten Daten können dann genutzt werden um, optimale, kürzeste Wege zu berechnen.

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تاریخ انتشار 2013