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Refined Mean Field Analysis: The Gossip Shuffle Protocol Revisited

Abstract : Gossip protocols form the basis of many smart collective adaptive systems. They are a class of fully decentralised, simple but robust protocols for the distribution of information throughout large scale networks with hundreds or thousands of nodes. Mean field analysis methods have made it possible to approximate and analyse performance aspects of such large scale protocols in an efficient way that is independent of the number of nodes in the network. Taking the gossip shuffle protocol as a benchmark, we evaluate a recently developed refined mean field approach. We illustrate the gain in accuracy this can provide for the analysis of medium size models analysing two key performance measures: replication and coverage. We also show that refined mean field analysis requires special attention to correctly capture the coordination aspects of the gossip shuffle protocol.
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https://hal.inria.fr/hal-03273995
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Submitted on : Tuesday, June 29, 2021 - 4:13:17 PM
Last modification on : Sunday, June 26, 2022 - 5:09:51 AM
Long-term archiving on: : Thursday, September 30, 2021 - 7:14:28 PM

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Nicolas Gast, Diego Latella, Mieke Massink. Refined Mean Field Analysis: The Gossip Shuffle Protocol Revisited. COORDINATION 2020 - 22nd IFIP WG 6.1 International Conference on Coordination Languages and Models, Jun 2020, Valletta, Malta. pp.230-239, ⟨10.1007/978-3-030-50029-0_15⟩. ⟨hal-03273995⟩

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