Server based route planning in road networks is now powerful enough to find quickest paths in a matter of milliseconds, even if detailed information on time-dependent travel times is taken into account. However this requires huge amounts of memory on each query server and hours of preprocessing even for a medium sized country like Germany. This is a problem since global internet companies would like to work with transcontinental networks, detailed models of intersections, and regular re-preprocessing that takes the current traffic situation into account. By giving a distributed memory parallelization of the arguably best current technique - time-dependent contraction hierarchies, we remove these bottlenecks. For example, on a medium size network 64 processes accelerate preprocessing by a factor of 28 to 160 seconds, reduce per process memory consumption by a factor of 10.5 and increase query throughput by a factor of 25. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Kieritz, T., Luxen, D., Sanders, P., & Vetter, C. (2010). Distributed time-dependent contraction hierarchies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6049 LNCS, pp. 94–105). https://doi.org/10.1007/978-3-642-13193-6_9
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