Local MST computation with short advice

Pierre Fraigniaud (1, 2) , Amos Korman (3) , Emmanuelle Lebhar (1, 2)

1 LIAFA - Laboratoire d'informatique Algorithmique : Fondements et Applications
2 GANG - Networks, Graphs and Algorithms
3 Technion - Israel Institute of Technology [Haifa]

We use the recently introduced advising scheme framework for measuring the difficulty of locally distributively computing a Minimum Spanning Tree (MST). An (m, t)-advising scheme for a distributed problem P is a way, for every possible input I of P , to provide an ”advice” (i.e., a bit string) about I to each node so that: (1) the maximum size of the advices is at most m bits, and (2) the problem P can be solved distributively in at most t rounds using the advices as inputs. In case of MST, the output returned by each node of a weighted graph G is the edge leading to its parent in some rooted MST T of G. Clearly, there is a trivial (log n

Mots clés: Minimum spanning tree; distributed algorithm; local computation

Domaines: Algorithme et structure de données [cs.DS]; Calcul parallèle, distribué et partagé [cs.DC]

Pierre Fraigniaud, Amos Korman, Emmanuelle Lebhar. Local MST computation with short advice. ACM Symposium on Parallel Algorithms and Architectures, Jun 2007, San Diego, United States. pp.154. ⟨hal-00154849⟩