Ivan Lavallée

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1. Introduction In this paper, we consider a connected undi-rected graph with n nodes. An asynchronous distributed algorithm is described which determines a spanning tree of the graph. Moreover, if the edges of the graph are weighted, the same algorithm can compute a minimum-weighted spanning tree. This algorithm can be favourably compared to the one of(More)
We introduce in this paper a competitive unsupervised clustering algorithm which has two strong features: it is fast and flexible on the processed data type as well as in terms of precision. Our approach has a computational cost, in the worst case, of O(n 2) + ε, and in the average case, of O(n) + ε. This complexity is due to the use of ultrametric distance(More)
This paper presents an asynchronous distributed algorithm for solving the maximum flow problem which is based on the preflow-push approach of Golberg-Tarjan. Each node in graph initially knows the capacities of outgoing and incoming adjacent arcs, the source nodes knows additionally the number of nodes in graph. Nodes execute the same algorithm, and(More)
We assume a link-register communication model under read/write atomicity, where every process can read from but cannot write into its neighbours' registers. The paper presents two self-stabilizing protocols for basic fair and reliable link communication primitives. The first primitive guarantees that any process writes a new value in its register(s) only(More)
Fast matrix multiplication (FMM) algorithms to multiply two n × n matrices reduce the asymptotic operation count from O(n3) of the traditional algorithm to O(n2.38), thus on distributed memory computers, the association of FMM algorithms and the parallel matrix multiplication algorithms always gives remarkable results. Within this association, the(More)