Schéma général auto-stabilisant et silencieux de constructions de type arbres couvrants

International audienceNous proposons un schéma général, appelé Scheme, qui calcule des structures de données de type arbres couvrants dans des réseaux quelconques. Scheme est auto-stabilisant, silencieux et malgré sa généralité, est aussi efficace. Il est écrit dans le modèle à mémoires localement partagées avec atomicité composite, et supposeun démon distribué inéquitable, l'hypothèse la plus faible concernant l'ordonnancement dans ce modèle. Son temps de stabilisation est d'au plus 4 nmax rondes, où nmax est le nombre maximum de processus dans une composante connexe. Nous montrons également des bornes supérieures polynomiales sur le temps de stabilisation en nombre de pas et de mouvements pour de grandes classes d'instances de l'algorithme Scheme. Nous illustrons la souplesse de notre approche en décrivant de telles instances résolvant des problèmes classiques tels que l'élection de leader et la construction d'arbres couvrants

Self-Stabilizing Disconnected Components Detection and Rooted Shortest-Path Tree Maintenance in Polynomial Steps

We deal with the problem of maintaining a shortest-path tree rooted at some process r in a network that may be disconnected after topological changes. The goal is then to maintain a shortest-path tree rooted at r in its connected component, V_r, and make all processes of other components detecting that r is not part of their connected component. We propose, in the composite atomicity model, a silent self-stabilizing algorithm for this problem working in semi-anonymous networks under the distributed unfair daemon (the most general daemon) without requiring any a priori knowledge about global parameters of the network. This is the first algorithm for this problem that is proven to achieve a polynomial stabilization time in steps. Namely, we exhibit a bound in O(W_{max} * n_{maxCC}^3 * n), where W_{max} is the maximum weight of an edge, n_{maxCC} is the maximum number of non-root processes in a connected component, and n is the number of processes. The stabilization time in rounds is at most 3n_{maxCC} + D, where D is the hop-diameter of V_r

Self-Stabilizing Distributed Cooperative Reset

Self-stabilization is a versatile fault-tolerance approach that characterizes the ability of a system to eventually resume a correct behavior after any finite number of transient faults. In this paper, we propose a self-stabilizing reset algorithm working in anonymous networks. This algorithm resets the network in a distributed non-centralized manner, i.e., it is multi-initiator, as each process detecting an inconsistency may initiate a reset. It is also cooperative in the sense that it coordinates concurrent reset executions in order to gain efficiency. Our approach is general since our reset algorithm allows to build self-stabilizing solutions for various problems and settings. As a matter of facts, we show that it applies to both static and dynamic specifications since we propose efficient self-stabilizing reset-based algorithms for the (1-minimal) (f, g)-alliance (a generalization of the dominating set problem) in identified networks and the unison problem in anonymous networks. Notice that these two latter instantiations enhance the state of the art. Indeed, in the former case, our solution is more general than the previous ones, while in the latter case, the complexity of our unison algorithm is better than that of previous solutions of the literature

Making local algorithms efficiently self-stabilizing in arbitrary asynchronous environments

This paper deals with the trade-off between time, workload, and versatility in self-stabilization, a general and lightweight fault-tolerant concept in distributed computing.In this context, we propose a transformer that provides an asynchronous silent self-stabilizing version Trans(AlgI) of any terminating synchronous algorithm AlgI. The transformed algorithm Trans(AlgI) works under the distributed unfair daemon and is efficient both in moves and rounds.Our transformer allows to easily obtain fully-polynomial silent self-stabilizing solutions that are also asymptotically optimal in rounds.We illustrate the efficiency and versatility of our transformer with several efficient (i.e., fully-polynomial) silent self-stabilizing instances solving major distributed computing problems, namely vertex coloring, Breadth-First Search (BFS) spanning tree construction, k-clustering, and leader election

Self-Stabilizing Leader Election in Polynomial Steps

International audienceWe propose a silent self-stabilizing leader election algorithm for bidirectional connected identified networks of arbitrary topology. This algorithm is written in the locally shared memory model. It assumes the distributed unfair daemon, the most general scheduling hypothesis of the model. Our algorithm requires no global knowledge on the network (such as an upper bound on the diameter or the number of processes, for example).We show that its stabilization time is in $\Theta(n^3)$ steps in the worst case, where $n$ is the number of processes. Its memory requirement is asymptotically optimal, i.e., $\Theta(\log n)$ bits per processes. Its round complexity is of the same order of magnitude --- i.e., $\Theta(n)$ rounds --- as the best existing algorithms designed with similar settings. To the best of our knowledge, this is the first self-stabilizing leader election algorithm for arbitrary identified networks that is proven to achieve a stabilization time polynomial in steps. By contrast, we show that the previous best existing algorithms designed with similar settings stabilize in a non polynomial number of steps in the worst case

Self-stabilizing leader election in polynomial steps

International audienc

Self-Stabilizing Leader Election in Polynomial Steps

International audienceWe propose a silent self-stabilizing leader election algorithm for bidirectional connected identified networks of arbitrary topology. This algorithm is written in the locally shared memory model. It assumes the distributed unfair daemon, the most general scheduling hypothesis of the model. Our algorithm requires no global knowledge on the network (such as an upper bound on the diameter or the number of processes, for example). We show that its stabilization time is in Θ(n^3) steps in the worst case, where n is the number of processes. Its memory requirement is asymptotically optimal, i.e., Θ(log n) bits per processes. Its round complexity is of the same order of magnitude — i.e., Θ(n) rounds — as the best existing algorithm (Datta et al, 2011) designed with similar settings. To the best of our knowledge, this is the first self-stabilizing leader election algorithm for arbitrary identified networks thatis proven to achieve a stabilization time polynomial in steps. By contrast, we show that the previous best existing algorithm designed with similar settings (Datta et al, 2011) stabilizes in a non polynomial number of steps in the worst case