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On the Uniformity of Peer Sampling based on View Shuffling

Abstract : Consider a group of peers, an ideal random peer sampling service should return a peer, which is a uniform independent random sample of the group. This paper focuses on the implementation and analysis of a peer sampling service based on symmetric view shuffling, where each peer is equipped with a local view of size c, representing a uniform random sample of size c of the whole system. To this end, pairs of peers regularly and continuously swap a part of their local views (shuffle operation). The paper provides the following formal proofs: (i) starting from any non-uniform distribution of peers in the peers' local views, after a sequence of pairwise shuffle operations, each local view eventually represents a uniform sample of size c; (ii) once previous property holds, any successive sequence of shuffle operations does not modify this uniformity property and (iii) a lower bound for convergence speed. This paper also presents some numerical results concerning the speed of convergence to uniform samples of the local views.
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Submitted on : Tuesday, June 7, 2022 - 3:37:08 PM
Last modification on : Wednesday, June 8, 2022 - 11:35:08 AM

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Yann Busnel, Roberto Beraldi, Roberto Baldoni. On the Uniformity of Peer Sampling based on View Shuffling. Journal of Parallel and Distributed Computing, Elsevier, 2011, 71 (8), pp.1165-1176. ⟨10.1016/j.jpdc.2011.01.009⟩. ⟨hal-03687435⟩

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