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Self-stabilizing Local k-Placement of Replicas with Minimal Variance

  • Sven Köhler
  • Volker Turau
  • Gerhard Mentges
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7596)

Abstract

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.

Keywords

Potential Function Load Balance Minimal Variance Malicious Node Load Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sven Köhler
    • 1
  • Volker Turau
    • 1
  • Gerhard Mentges
    • 1
  1. 1.Institute of TelematicsHamburg University of TechnologyHamburgGermany

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