Phase transition of the k -majority dynamics in biased communication models

PROCEEDINGS OF THE 2021 INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING AND NETWORKING (ICDCN '21)(2023)

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摘要
Consider a graph where each of the n nodes is either in state ℛ or ℬ . Herein, we analyze the synchronous k - Majority dynamics , where in each discrete-time round nodes simultaneously sample k neighbors uniformly at random with replacement and adopt the majority state among those of the nodes in the sample (breaking ties uniformly at random). Differently from previous work, we study the robustness of the k - Majority in maintaining a ℛ majority , when the dynamics is subject to two forms of bias toward state ℬ . The bias models an external agent that attempts to subvert the initial majority by altering the communication between nodes, with a probability of success p in each round: in the first form of bias, the agent tries to alter the communication links by transmitting state ℬ ; in the second form of bias, the agent tries to corrupt nodes directly by making them update to ℬ . Our main result shows a sharp phase transition in both forms of bias. By considering initial configurations in which every node has probability q ∈ (1/2,1] of being in state ℛ , we prove that for every k≥ 3 there exists a critical value p_k,q^⋆ such that, with high probability, the external agent is able to subvert the initial majority either in n^ω (1) rounds, if pp_k,q^⋆ . When k<3 , instead, no phase transition phenomenon is observed and the disruption happens in O (1) rounds for p>0 .
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关键词
Biased Communication, Consensus, Majority Dynamics, Markov Chains, Metastability
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