Better Distance Labeling for Unweighted Planar Graphs

Abstract

A distance labeling scheme is an assignment of labels, that is, binary strings, to all nodes of a graph, so that the distance between any two nodes can be computed from their labels without any additional information about the graph. The goal is to minimize the maximum length of a label as a function of the number of nodes. A major open problem in this area is to determine the complexity of distance labeling in unweighted planar (undirected) graphs. It is known that, in such a graph on n nodes, some labels must consist of varOmega (n^{1/3}) bits, but the best known labeling scheme constructs labels of length O(sqrt{n}log n) (Gavoille, Peleg, Pérennes, and Raz in J Algorithms 53:85–112, 2004). For weighted planar graphs with edges of length polynomial in n, we know that labels of length varOmega (sqrt{n}log n) are necessary (Abboud and Dahlgaard in FOCS, 2016). Surprisingly, we do not know if distance labeling for weighted planar graphs with edges of length polynomial in n is harder than distance labeling for unweighted planar graphs. We prove that this is indeed the case by designing a distance labeling scheme for unweighted planar graphs on n nodes with labels consisting of O(sqrt{n}) bits with a simple and (in our opinion) elegant method. We also show how to extend this to graphs with small weight and (unweighted) graphs with bounded genus. We augment the construction for unweighted planar graphs with a mechanism (based on Voronoi diagrams) that allows us to compute the distance between two nodes in only polylogarithmic time while increasing the length to O(sqrt{nlog n}). The previous scheme required varOmega (sqrt{n}) time to answer a query in this model.