Analysis of Farthest Point Sampling for Approximating Geodesics in a Graph
Résumé
A standard way to approximate the distance between
two vertices $p$ and $q$ in a graph is to
compute
a shortest path from $p$ to $q$ that goes through one of $k$ sources, which are well-chosen
vertices. Precomputing the distance between each of the $k$ sources to all vertices
yields an efficient computation of approximate distances between any two vertices. One standard method for choosing $k$ sources is the so-called {\it Farthest Point Sampling} (FPS), which starts with a random vertex as the first source, and iteratively selects the farthest vertex from the already selected sources.
In this paper, we analyze the stretch factor $\mathcal{F}_{\text{FPS}}$
of approximate geodesics computed using FPS, which is the maximum, over all pairs of distinct
vertices, of their approximated distance over their geodesic distance in the graph. We show that
$\mathcal{F}_{\text{FPS}}$ can be bounded in terms of the minimal value $\mathcal{F}^\ast$ of the
stretch factor obtained using an optimal placement of $k$ sources as $\mathcal{F}_{\text{FPS}}\leq 2
r_e^2 \mathcal{F}^\ast+ 2 r_e^2 + 8 r_e + 1$, where $r_e$ is the length ratio of
longest edge over the shortest edge in the graph.
We further show that the factor $r_e$
is not an artefact of the analysis by providing a class of graphs for which
$\mathcal{F}_{\text{FPS}} \geq \frac{1}{2} r_e \mathcal{F}^\ast$.
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