Gossip-based peer sampling

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How researchers see this paper

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Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs (2019, background): “In a decentralized system, this can be implemented by a classic primitive known as a peer sampling service (Jelasity et al., 2007; Kermarrec et al., 2011).”
Private Similarity Computation in Distributed Systems: From Cryptography to Differential Privacy (2011, unknown): “We consider a distributed system of n nodes, connected via an unstructured network [17].”
Want to scale in centralized systems? Think P2P (2015, methodology): “Periodically, each protocol selects the entry in its view with the oldest timestamp [45] and sends it a message containing its profile with part (or all) of its view.”
WHATSUP: A Decentralized Instant News Recommender (2013, background): “The union of the RPS views represents a continuously changing random graph [4].”
HyRec: leveraging browsers for scalable recommenders (2014, methodology): “A fully decentralized architecture, e.g. [19, 21, 18], builds an overlay network comprising all user machines, typically resembling a uniform random graph topology [35].”
Converging Quickly to Independent Uniform Random Topologies (2011, background): “Therefore, ideally, any node exchanges information with peers that are selected following a uniform random sample of all nodes in the system [1], [5], [6], [7].”
PeerSim: A scalable P2P simulator (2009, background): “One strong feature of PEERSIM is its graph abstraction.”