Lower bounds in the preprocessing and query phases of routing algorithms
C White - Algorithms-ESA 2015: 23rd Annual European …, 2015 - Springer
Algorithms-ESA 2015: 23rd Annual European Symposium, Patras, Greece, September …, 2015•Springer
In the last decade, there has been a substantial amount of research in finding routing
algorithms designed specifically to run on real-world graphs. In 2010, Abraham et al.
showed upper bounds on the query time in terms of a graph's highway dimension and
diameter for the current fastest routing algorithms, including contraction hierarchies, transit
node routing, and hub labeling. In this paper, we show corresponding lower bounds for the
same three algorithms. We also show how to improve a result by Milosavljević which lower …
algorithms designed specifically to run on real-world graphs. In 2010, Abraham et al.
showed upper bounds on the query time in terms of a graph's highway dimension and
diameter for the current fastest routing algorithms, including contraction hierarchies, transit
node routing, and hub labeling. In this paper, we show corresponding lower bounds for the
same three algorithms. We also show how to improve a result by Milosavljević which lower …
Abstract
In the last decade, there has been a substantial amount of research in finding routing algorithms designed specifically to run on real-world graphs. In 2010, Abraham et al. showed upper bounds on the query time in terms of a graph’s highway dimension and diameter for the current fastest routing algorithms, including contraction hierarchies, transit node routing, and hub labeling. In this paper, we show corresponding lower bounds for the same three algorithms. We also show how to improve a result by Milosavljević which lower bounds the number of shortcuts added in the preprocessing stage for contraction hierarchies. We relax the assumption of an optimal contraction order (which is NP-hard to compute), allowing the result to be applicable to real-world instances. Finally, we give a proof that optimal preprocessing for hub labeling is NP-hard. Hardness of optimal preprocessing is known for most routing algorithms, and was suspected to be true for hub labeling.
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