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Title: Byzantine Consensus with Local Multicast Channels
Byzantine consensus is a classical problem in distributed computing. Each node in a synchronous system starts with a binary input. The goal is to reach agreement in the presence of Byzantine faulty nodes. We consider the setting where communication between nodes is modelled via an undirected communication graph. In the classical point-to-point communication model all messages sent on an edge are private between the two endpoints of the edge. This allows a faulty node to equivocate, i.e., lie differently to its different neighbors. Different models have been proposed in the literature that weaken equivocation. In the local broadcast model, every message transmitted by a node is received identically and correctly by all of its neighbors. In the hypergraph model, every message transmitted by a node on a hyperedge is received identically and correctly by all nodes on the hyperedge. Tight network conditions are known for each of the three cases. We introduce a more general model that encompasses all three of these models. In the local multicast model, each node u has one or more local multicast channels. Each channel consists of multiple neighbors of u in the communication graph. When node u sends a message on a channel, it is received identically by all of its neighbors on the channel. For this model, we identify tight network conditions for consensus. We observe how the local multicast model reduces to each of the three models above under specific conditions. In each of the three cases, we relate our network condition to the corresponding known tight conditions. The local multicast model also encompasses other practical network models of interest that have not been explored previously, as elaborated in the paper.  more » « less
Award ID(s):
1733872
NSF-PAR ID:
10309774
Author(s) / Creator(s):
Editor(s):
Gilbert, Seth
Date Published:
Journal Name:
Leibniz international proceedings in informatics
Volume:
209
ISSN:
1868-8969
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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