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Improving Gossip Dynamics Through Overlapping Replicates

  • Danilo PianiniEmail author
  • Jacob Beal
  • Mirko Viroli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9686)

Abstract

Gossip protocols are a fast and effective strategy for computing a wide class of aggregate functions involving coordination of large sets of nodes. The monotonic nature of gossip protocols, however, mean that they can typically only adjust their estimate in one direction unless restarted, which disrupts the values being returned. We propose to improve the dynamical performance of gossip by running multiple replicates of a gossip algorithm, overlapping in time. We find that this approach can significantly reduce the error of aggregate function estimates compared to both typical gossip implementations and tree-based estimation functions.

Keywords

Aggregate Function Prior Method Network Diameter Algorithm Instance Circular Arena 
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

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  1. 1.Alma Mater Studiorum–Università di BolognaCesenaItaly
  2. 2.Raytheon BBN TechnologiesCambridgeUSA

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