Distributed Multivalued Consensus
Motivated by the distributed binary consensus algorithm in  we propose a distributed algorithm for the multivalued consensus problem. In multivalued consensus problem, each node initially chooses from one of k available choices and the objective of all nodes is to find the choice which was initially chosen by the majority in a distributed fashion. Although the voter model (e.g. ) can be used to find a consensus on multiple choices, it only guarantees the consensus and not the consensus on the majority. We derive the time of convergence and an upper bound for the probability of error of our proposed algorithm which shows that, similar to , having an additional state would result in significant improvement of both convergence time and probability of error for complete graphs. We also show that our algorithm could be used in Erdos-Renyi and regular graphs by using simulations.
Moez Draief is supported by QNRF through NPRP grant number 09-1150-2-148.
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