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A distributed clustering algorithm for large-scale dynamic networks

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Abstract

We propose an algorithm that builds and maintains clusters over a network subject to mobility. This algorithm is fully decentralized and makes all the different clusters grow concurrently. The algorithm uses circulating tokens that collect data and move according to a random walk traversal scheme. Their task consists in (i) creating a cluster with the nodes it discovers and (ii) managing the cluster expansion; all decisions affecting the cluster are taken only by a node that owns the token. The size of each cluster is maintained higher than m nodes (m is a parameter of the algorithm). The obtained clustering is locally optimal in the sense that, with only a local view of each clusters, it computes the largest possible number of clusters (i.e. the sizes of the clusters are as close to m as possible). This algorithm is designed as a decentralized control algorithm for large scale networks and is mobility-adaptive: after a series of topological changes, the algorithm converges to a clustering. This recomputation only affects nodes in clusters where topological changes happened, and in adjacent clusters.

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Authors and Affiliations

  1. CReSTIC, Université de Reims Champagne Ardenne, Reims, France

    Thibault Bernard

  2. PRiSM, CNRS and Université de Versailles Saint-Quentin-en-Yvelines, Versailles, France

    Alain Bui, Laurence Pilard & Devan Sohier

Authors
  1. Thibault Bernard
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  2. Alain Bui
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  3. Laurence Pilard
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  4. Devan Sohier
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Correspondence to Alain Bui.

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Bernard, T., Bui, A., Pilard, L. et al. A distributed clustering algorithm for large-scale dynamic networks. Cluster Comput 15, 335–350 (2012). https://doi.org/10.1007/s10586-011-0153-z

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  • DOI: https://doi.org/10.1007/s10586-011-0153-z

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