A distance labeling scheme is an assignment of bit-labels to the vertices of
an undirected, unweighted graph such that the distance between any pair of
vertices can be decoded solely from their labels. An important class of
distance labeling schemes is that of hub labelings, where a node v∈G
stores its distance to the so-called hubs Sv⊆V, chosen so that for
any u,v∈V there is w∈Su∩Sv belonging to some shortest uv
path. Notice that for most existing graph classes, the best distance labelling
constructions existing use at some point a hub labeling scheme at least as a
key building block. Our interest lies in hub labelings of sparse graphs, i.e.,
those with ∣E(G)∣=O(n), for which we show a lowerbound of
2O(logn)n for the average size of the hubsets.
Additionally, we show a hub-labeling construction for sparse graphs of average
size O(RS(n)cn) for some 0<c<1, where RS(n) is the
so-called Ruzsa-Szemer{\'e}di function, linked to structure of induced
matchings in dense graphs. This implies that further improving the lower bound
on hub labeling size to 2(logn)o(1)n would require a
breakthrough in the study of lower bounds on RS(n), which have resisted
substantial improvement in the last 70 years. For general distance labeling of
sparse graphs, we show a lowerbound of 2O(logn)1SumIndex(n), where SumIndex(n) is the communication complexity of the
Sum-Index problem over Zn. Our results suggest that the best achievable
hub-label size and distance-label size in sparse graphs may be
Θ(2(logn)cn) for some 0<c<1