Abstract
In this paper, we consider lightweight decentralised algorithms for achieving consensus in distributed systems. Each member of a distributed group has a private value from a fixed set consisting of, say, two elements, and the goal is for all members to reach consensus on the majority value. We explore variants of the voter model applied to this problem. In the voter model, each node polls a randomly chosen group member and adopts its value. The process is repeated until consensus is reached. We generalise this so that each member polls a (deterministic or random) number of other group members and changes opinion only if a suitably defined super-majority has a different opinion. We show that this modification greatly speeds up the convergence of the algorithm, as well as substantially reducing the probability of it reaching consensus on the incorrect value.
Original language | English |
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Pages (from-to) | 99-120 |
Number of pages | 22 |
Journal | Queueing Systems |
Volume | 78 |
Issue number | 2 |
Early online date | 23 Mar 2014 |
DOIs | |
Publication status | Published - Oct 2014 |
Keywords
- Consensus
- Markov chains
- Probability
- Voter model
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Dr A J Ganesh
- School of Mathematics - Associate Professor
- Statistical Science
- Probability, Analysis and Dynamics
- Cabot Institute for the Environment
- Probability
Person: Academic , Member