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International audience; We consider the problem of periodic graph exploration in which a mobile entity with constant memory, an agent, has to visit all n nodes of an input simple, connected, undirected graph in a periodic manner. Graphs are assumed to be anonymous, that is, nodes are unlabeled. While visiting a node, the agent may distinguish between the edges incident to it; for each node v, the endpoints of the edges incident to v are uniquely identified by different integer labels called port numbers. We are interested in algorithms for assigning the port numbers together with traversal algorithms for agents using these port numbers to obtain short traversal periods. Periodic graph exploration is unsolvable if the port numbers are set arbitrarily; see Budach (1978) [1]. However, surprisingly small periods can be achieved by carefully assigning the port numbers. Dobrev et al. (2005) [4] described an algorithm for assigning port numbers and an oblivious agent (i.e., an agent with no memory) using it, such that the agent explores any graph with n nodes within the period 10n. When the agent has access to a constant number of memory bits, the optimal length of the period was proved in Gąsieniec et al. (2008) [7] to be no more than 3.75n−2 (using a different assignment of the port numbers and a different traversal algorithm). In this paper, we improve both these bounds. More precisely, we show how to achieve a period length of at most for oblivious agents and a period length of at most 3.5n−2 for agents with constant memory. To obtain our results, we introduce a new, fast graph decomposition technique called a three-layer partition that may also be useful for solving other graph problems in the future. Finally, we present the first non-trivial lower bound, 2.8n−2, on the period length for the oblivious case.

International audience; 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 counterparts for undirected graphs 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 diam within time O(diam|E|), and in the long run traverses all edges of G with the same frequency.

International audience; In the effort to understand the algorithmic limitations of computing by a swarm of robots, the research has focused on the minimal capabilities that allow a problem to be solved. The weakest of the commonly used models is {\sc Asynch} where the autonomous mobile robots, endowed with visibility sensors (but otherwise unable to communicate), operate in Look-Compute-Move cycles performed asynchronously for each robot. The robots are often assumed (or required to be) oblivious: they keep no memory of observations and computations made in previous cycles. We consider the setting when the robots are dispersed in an anonymous and unlabeled graph, and they must perform the very basic task of {\em exploration}: within finite time every node must be visited by at least one robot and the robots must enter a quiescent state. The complexity measure of a solution is the number of robots used to perform the task. We study the case when the graph is an arbitrary tree and establish some unexpected results. We first prove that, in general, exploration cannot be done efficiently. More precisely we prove that there are $n$-node trees where $\Omega(n)$ robots are necessary; this holds even if the maximum degree is $4$. On the other hand, we show that if the maximum degree is $3$, it is possible to explore with only $O(\frac{\log n} {\log\log n})$ robots. The proof of the result is constructive. We also prove that the size of the team used in our solution is asymptotically {\em optimal}: there are trees of degree $3$, whose exploration requires $\Omega(\frac{\log n}{\log\log n})$ robots. Our final result shows that the difficulty in tree exploration comes in fact from the symmetries of the tree. Indeed, we show that, in order to explore trees that do not have any non-trivial automorphisms, 4 robots are always sufficient and often necessary.

International audience; A group of mobile robots (beachcombers) have to search collectively every point of a given domain. At any given moment, each robot can be in {\em walking mode} or in {\em searching mode}. It is assumed that each robot's maximum allowed searching speed is strictly smaller than its maximum allowed walking speed. A point of the domain is searched if at least one of the robots visits it in searching mode. The Beachcombers' Problem consists in developing efficient {\em schedules} (algorithms) for the robots which collectively search all the points of the given domain as fast as possible. We consider searching schedules in the following one-dimensional geometric domains: the cycle of a known circumference $L$, the finite straight line segment of a known length $L$, and the semi-infinite line $[0,+\infty)$.We first consider the {\em online} Beachcombers' Problem (i.e.~the scenario when the robots do not know in advance the length of the segment to be searched), where the robots are initially collocated at the origin of a semi-infinite line. It is sought to design a schedule $A$ with maximum {\em speed} $S$, defined as $S = \inf_{\ell}{\frac{\ell}{t_A(\ell)}}$, where $t_A(\ell)$ denotes the time when the search of the segment $[0,\ell]$ is completed under $A$. We consider a {\em discrete} and a {\em continuous} version of the problem, depending on whether the infimum is takenover $\ell \in \mathbb{N}^*$ or $\ell \geq 1$. We prove that the $\mathtt{LeapFrog}$ algorithm, which was proposed in [Czyzowicz et al., SIROCCO 2014, LNCS 8576, pp. 23--36 (2014)], is in fact optimal in the discrete case. This settles in the affirmative a conjecture from that paper. We also show how to extend this result to the more general continuous online setting.For the {\em offline} version of the Beachcombers' Problem (i.e.~the scenario when the robots know in advance the length of the segment to be searched), we consider the \emph{$t$-source} Beachcombers' Problem (i.e.~all robots start from a fixed number $t \geq 1$ of starting positions) on the cycle and on the finite segment. For the \emph{$t$-source} Beachcombers' Problem on the cycle, we show that the structure of the optimal solutions is identical to the structure of the optimal solutions to the $2t$-source Beachcombers' Problem on a finite segment. In consequence, by using results from [Czyzowicz et al., ALGOSENSORS 2014, LNCS 8847, pp.~3--21 (2014)], we prove that the \emph{1-source} Beachcombers' Problem on the cycle is NP-hard, and we derive approximation algorithms for the problem. For the \emph{$t$-source} variant of the Beachcombers' Problem on the cycle and on the finite segment, we also derive efficient approximation algorithms.One important contribution of our work is that, in all variants of the offline Beachcombers' Problem that we discuss, we allow the robots to \emph{change direction of movement} and search points of the domain on both sides of their respective starting positions. This represents a significant generalization compared to the model considered in~[Czyzowicz et al., ALGOSENSORS 2014, LNCS 8847, pp. 3--21 (2014)], in which each robot had a fixed direction of movement that was specified as part of the solution to the problem. We manage to prove that changes of direction do not help the robots achieve optimality.

International audience; We study the problem of exploration by a mobile entity (agent) of a class of dynamic networks, namely constantly connected dynamic graphs. This problem has already been studied in the case where the agent knows the dynamics of the graph and the underlying graph is a ring of $n$ vertices \cite{IW13}. In this paper, we consider the same problem and we suppose that the underlying graph is a cactus graph (a connected graph in which any two simple cycles have at most one vertex in common). We propose an algorithm that allows the agent to explore these dynamic graphs in at most $2^{O(\sqrt{\log n})} n$ time units. We show that the lower bound of the algorithm is $2^{\Omega(\sqrt{\log n})} n$ time units.

International audience; We present a distributed asynchronous algorithm that, for every undirected weighted $n$-node graph $G$, constructs name-independent routing tables for $G$. The size of each table is $\tO(\sqrt{n}\,)$, whereas the length of any route is stretched by a factor of at most~$7$ w.r.t. the shortest path. At any step, the memory space of each node is $\tO(\sqrt{n}\,)$. The algorithm terminates in time $O(D)$, where $D$ is the hop-diameter of $G$. In synchronous scenarios and with uniform weights, it consumes $\tO(m\sqrt{n} + n^{3/2}\min\set{D,\sqrt{n}\,})$ messages, where $m$ is the number of edges of $G$. In the realistic case of sparse networks of poly-logarithmic diameter, the communication complexity of our scheme, that is $\tO(n^{3/2})$, improves by a factor of $\sqrt{n}$ the communication complexity of \emph{any} shortest-path routing scheme on the same family of networks. This factor is provable thanks to a new lower bound of independent interest.

In this paper, we study the T-interval-connected dynamic graphs from the point of view of the time necessary and sufficient for their exploration by a mobile entity (agent). A dynamic graph (more precisely, an evolving graph) is T-interval-connected (T ≥ 1) if, for every window of T consecutive time steps, there exists a connected spanning subgraph that is stable (always present) during this period. This property of connection stability over time was introduced by Kuhn, Lynch and Oshman (Kuhn et al. 14) (STOC 2010). We focus on the case when the underlying graph is a ring of size n, and we show that the worst-case time complexity for the exploration problem is 2n − T − Θ(1) time units if the agent knows the dynamics of the graph, and $n+ \frac {n}{\max \{1, T-1\} } (\delta -1) \pm {\Theta }(\delta )$ time units otherwise, where δ is the maximum time between two successive appearances of an edge.

International audience; The rotor-router model, also called the Propp machine, was first considered as a deterministic alternative to the random walk. It is known that the route in an undirected graph G=(V,E), where |V|=n and |E|=m, adopted by an agent controlled by the rotor-router mechanism forms eventually an Euler tour based on arcs obtained via replacing each edge in G by two arcs with opposite direction. The process of ushering the agent to an Euler tour is referred to as the lock-in problem. In recent work [Yan03] Yanovski et al. proved that independently of the initial configuration of the rotor-router mechanism in G the agent locks-in in time bounded by 2m diam, where diam is the diameter of G. This upper bound can be matched asymptotically in lollipop graphs. In this paper we examine the dependence of the lock-in time on the initial configuration of the rotor-router mechanism. The case study is performed in the form of a game between a player pl intending to lock-in the agent in an Euler tour as quickly as possible and its adversary ad with the counter objective. First, we observe that in certain (easy) cases the lock-in can be achieved in time O(m). On the other hand we show that if adversary ad is solely responsible for the assignment of ports and pointers, the lock-in time Omega(m diam) can be enforced in any graph with m edges and diameter diam. Furthermore, we show that if ad provides its own port numbering after the initial setup of pointers by pl, the complexity of the lock-in problem is bounded by O(m min{log m,diam}). We also propose a class of graphs in which the lock-in requires time Omega(m log m). In the remaining two cases we show that the lock-in requires time Omega(m diam) in graphs with the worst-case topology. In addition, however, we present non-trivial classes of graphs with a large diameter in which the lock-in time is O(m).

We consider the task of exploring graphs with anonymous nodes by a team of non-cooperative robots, modeled as finite automata. For exploration to be completed, each edge of the graph has to be traversed by at least one robot. In this paper, the robots have no a priori knowledge of the topology of the graph, nor of its size, and we are interested in the amount of memory the robots need to accomplish exploration, We introduce the so-called {\em reduced automata technique}, and we show how to use this technique for deriving several space lower bounds for exploration. Informally speaking, the reduced automata technique consists in reducing a robot to a simpler form that preserves its “core” behavior on some graphs. Using this technique, we first show that any set of $q\geq 1$ non-cooperative robots, requires $\Omega(\log(\frac{n}{q}))$ memory bits to explore all $n$-node graphs. The proof implies that, for any set of $q K$-state robots, there exists a graph of size $O(qK)$ that no robot of this set can explore, which improves the $O(K^{O(q)})$ bound by Rollik (1980). Our main result is an application of this latter result, concerning {\em terminating} graph exploration with one robot, i.e., in which the robot is requested to stop after completing exploration. For this task, the robot is provided with a pebble, that it can use to mark nodes (without such a marker, even terminating exploration of cycles cannot be achieved). We prove that terminating exploration requires $\Omega(\log n)$ bits of memory for a robot achieving this task in all $n$-node graphs.