Self-stabilizing local k-placement of replicas with minimal variance.
Volker Turau
08 December 2014, 15h30 Salle/Bat : 445/PCRI-N
Contact :
Activités de recherche : Algorithmique distribuée
Résumé :
Large scale distributed systems require replication of resources to
amplify availability and to provide fault tolerance. The placement of
replicated resources significantly impacts performance. This paper
considers local k-placements: Each node of a network has to place k
replicas of a resource among its direct neighbors. The load of a node in
a given local k-placement is the number of replicas it stores. The local
k-placement problem is to achieve a preferably homogeneous distribution
of the loads. We present a novel self-stabilizing, distributed,
asynchronous, scalable algorithm for the k-placement problem such that
the standard deviation of the distribution of the loads assumes a local
minimum.
