Derandomizing Random Walks in Undirected Graphs Using Locally Fair Exploration Strategies

Abstract

We consider the problem of exploring an anonymous undirected graph using an oblivious robot. The studied exploration strategies are designed so that the next edge in the robot’s walk is chosen using only local information, and so that some local equity (fairness) criterion is satisfied for the adjacent undirected edges. Such strategies can be seen as an attempt to derandomize random walks, and are natural undirected counterparts of the rotor-router model for symmetric directed graphs.

The first of the studied strategies, known as Oldest-First (OF), always chooses the neighboring edge for which the most time has elapsed since its last traversal. Unlike in the case of symmetric directed graphs, we show that such a strategy in some cases leads to exponential cover time. We then consider another strategy called Least-Used-First (LUF) which always uses adjacent edges which have been traversed the smallest number of times. We show that any Least-Used-First exploration covers a graph G = (V,E) of diameter $\mathit{D}$ within time $O(\mathit{D}|E|)$, and in the long run traverses all edges of G with the same frequency.

The research was partially funded by the KBN (Poland) Grant 4 T11C 047 25, by the ANR projects “ALADDIN” and “ALPAGE”, by the INRIA project “CEPAGE”, and by European COST Action Action 295 “Dynamic Communication Networks” (DYNAMO).