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We consider the problem of constructing a maximum independent set with mobile myopic luminous robots on a grid network whose size is finite but unknown to the robots. In this setting, the robots enter the grid network one by one from a corner of the grid, and they eventually have to be disseminated on the grid nodes so that the occupied positions form a maximum independent set of the network. We assume that robots are asynchronous, anonymous, silent and they execute the same distributed algorithm. In this paper, we propose two algorithms: The first one assumes that the number of light colors of each robot is three and the visible range is two, but uses the additional assumption that a local edge-labeling exists for each node. To remove this assumption, the second one assumes that the number of light colors of each robot is seven, and that the visible range is three. In both algorithms, the number of movements is |$O(n(L+l))$| steps, where |$n$| is the number of nodes and |$L$| and |$l$| are the grid dimensions. [ABSTRACT FROM AUTHOR]

We consider swarms of asynchronous oblivious robots evolving into an anonymous grid-shaped network. In this context, we investigate optimal (w.r.t. the number of robots) deterministic solutions for the terminating exploration problem. We first show lower bounds in the semi-synchronous model. Precisely, we show that at least three robots are required to explore any grid of at least three nodes, even in the probabilistic case. Then, we show that at least four (resp. five) robots are necessary to deterministically explore a |$\bf(2,2)$| -Grid (resp. a |$\bf(3,3)$| -Grid). We then propose deterministic algorithms in the asynchronous model. This latter being strictly weakest than the semi-synchronous model, all the aforementioned bounds still hold in that context. Our algorithms actually exhibit the optimal number of robots that is necessary to explore a given grid. Overall, our results show that except in two particular cases, three robots are necessary and sufficient to deterministically explore a grid of at least three nodes and then terminate. The optimal number of robots for the two remaining cases is four for the |$\bf(2,2)$| -Grid and five for the |$\bf(3,3)$| -Grid, respectively. [ABSTRACT FROM AUTHOR]

The minimum spanning tree (MST) construction is a classical problem in Distributed Computing for creating a globally minimized structure distributedly. Self-stabilization is versatile technique for forward recovery that permits to handle any kind of transient faults in a unified manner. The loop-free property provides interesting safety assurance in dynamic networks where edge-cost changes during operation of the protocol.We present a new self-stabilizing MST protocol that improves on previous known approaches in several ways. First, it makes fewer system hypotheses as the size of the network (or an upper bound on the size) need not be known to the participants. Secondly, it is loop-free in the sense that it guarantees that a spanning tree structure is always preserved while edge costs change dynamically and the protocol adjusts to a new MST. Finally, time complexity matches the best known results, while space complexity results show that this protocol is the most efficient to date. [ABSTRACT FROM AUTHOR]

A self-stabilizing algorithm, regardless of the initial system state, converges in finite time to a set of states that satisfy a legitimacy predicate. The mutual exclusion problem is fundamental in distributed computing, since it allows processors competing to access a shared resource to be able to synchronize and get exclusive access to the resource (i.e. execute their critical section). It is well known that providing self-stabilization in general uniform networks (e.g. anonymous rings of arbitrary size) can only be probabilistic. However, all existing uniform probabilistic self-stabilizing mutual exclusion algorithms designed to work under an unfair distributed scheduler (that may choose processors to execute their code in an arbitrary manner) suffer from the following common drawback: once stabilized, there exists no upper bound on time between two successive executions of the critical section at a given processor. In this paper, we present the first self-stabilizing algorithm that guarantees such a bound (O(n³), where n is the network size) while working using an unfair distributed scheduler. Our algorithm works in an anonymous unidirectional ring of any size and has a polynomial expected stabilization time. [ABSTRACT FROM AUTHOR]