Self-stabilizing local k-placement of replicas with local minimum variance

S. Köhler, V. Turau

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)15-27
Number of pages13
JournalTheoretical Computer Science
StatePublished - 2 Aug 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier B.V.


  • Backup placement
  • Replication
  • Self-stabilizing algorithms


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