Introduction to distributed algorithms

TL;DR: It is shown that lohgic variables can easily be added to the more restricted models of Java and ML, thus providing an alternative way to do concurent programming in these languages.

TL;DR: This work gives a new synchronous distributed algorithm to find a k-dominating set in G of size no greater than [n/(k+1]], which has the same time complexity as the best currently known algorithm, but improves on that algorithm's message complexity and is, in addition, conceptually simpler.

TL;DR: This paper presents an asynchronous distributed algorithm for solving the maximum flow problem which is based on the preflow-push approach of Golberg-Tarjan, and takes O(n2m) message complexity and O( n2 ) time complexity.

TL;DR: In this article, the authors decrivons la problematique en jeu, nous passons en revue les solutions which ont ete proposees dans la litterature, en analysant leurs avantages and inconvenients.

TL;DR: A theoretical explanation for the observed behavior of the Vicsek model, which proves to be a graphic example of a switched linear system which is stable, but for which there does not exist a common quadratic Lyapunov function.

TL;DR: In a recent Physical Review Letters article, Vicsek et al. provide simulation results which demonstrate that the nearest neighbor rule they are studying can cause all agents to eventually move in the same direction despite the absence of centralized coordination and despite the fact that each agent's set of nearest neighbors change with time as the system evolves.

TL;DR: In this article, the authors consider a group of individuals who must act together as a team or committee, and assume that each individual in the group has his own subjective probability distribution for the unknown value of some parameter.

TL;DR: It is observed that more communication does not necessarily lead to faster convergence and may eventually even lead to a loss of convergence, even for the simple models discussed in the present paper.