MaxCUCL: Max-Consensus with Deterministic Convergence in Networks with Unreliable Communication
CoRR(2024)
摘要
In this paper, we present a novel distributed algorithm (herein called
MaxCUCL) designed to guarantee that max-consensus is reached in networks
characterized by unreliable communication links (i.e., links suffering from
packet drops). Our proposed algorithm is the first algorithm that achieves
max-consensus in a deterministic manner (i.e., nodes always calculate the
maximum of their states regardless of the nature of the probability
distribution of the packet drops). Furthermore, it allows nodes to determine
whether convergence has been achieved (enabling them to transition to
subsequent tasks). The operation of MaxCUCL relies on the deployment of
narrowband error-free feedback channels used for acknowledging whether a packet
transmission between nodes was successful. We analyze the operation of our
algorithm and show that it converges after a finite number of time steps.
Finally, we demonstrate our algorithm's effectiveness and practical
applicability by applying it to a sensor network deployed for environmental
monitoring.
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