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Fair Comparison of Gossip Algorithms over Large-Scale Random Topologies

Ruijing Hu 1 Julien Sopena 1 Luciana Arantes 1 Pierre Sens 1 Isabelle Demeure 2
1 Regal - Large-Scale Distributed Systems and Applications
LIP6 - Laboratoire d'Informatique de Paris 6, Inria Paris-Rocquencourt
Abstract : We present a thorough performance comparison of three widely used probabilistic gossip algorithms over well-known random graphs. These graphs represent some large-scale network topologies: Bernoulli (or Erdos-Rényi) graph, random geometric graph, and scale-free graph. In order to conduct such a fair comparison, particularly in terms of reliability, we propose a new parameter, called effectual fan out. For a given topology and gossip algorithm, the effectual fan out characterizes the mean dissemination power of infected sites. For large-scale networks, the effectual fan out has thus a strong linear correlation with message complexity. It enables to make an accurate analysis of the behavior of a gossip algorithm over a topology. Furthermore, it simplifies the theoretical comparison of different gossip algorithms on the topology. Based on extensive experiments on top of OMNet++ simulator, which make use of the effectual fan out, we discuss the impact of topologies and gossip algorithms on performance, and how to combine them to have the best gain in terms of reliability.
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Ruijing Hu, Julien Sopena, Luciana Arantes, Pierre Sens, Isabelle Demeure. Fair Comparison of Gossip Algorithms over Large-Scale Random Topologies. SRDS 2012 - 31th IEEE International Symposium on Reliable Distributed Systems, Oct 2012, Irvine, California, United States. pp.331-340, ⟨10.1109/SRDS.2012.28⟩. ⟨hal-01273261⟩



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