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

Authors:
Sven Köhler;Volker Turau;Gerhard Mentges
Affiliations:
Institute of Telematics, Hamburg University of Technology, Hamburg, Germany;Institute of Telematics, Hamburg University of Technology, Hamburg, Germany;Institute of Telematics, Hamburg University of Technology, Hamburg, Germany
Venue:
SSS'12 Proceedings of the 14th international conference on Stabilization, Safety, and Security of Distributed Systems
Year:
2012

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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.