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Population protocols are a model for distributed computing that is focused onsimplicity and robustness. A system of $n$ identical agents (finite statemachines) performs a global task like electing a unique leader or determiningthe majority opinion when each agent has one of two opinions. Agentscommunicate in pairwise interactions with randomly assigned communicationpartners. Quality is measured in two ways: the number of interactions tocomplete the task and the number of states per agent. We present protocols forthe majority problem that allow for a trade-off between these two measures.Compared to the only other trade-off result [Alistarh, Gelashvili, Vojnovic;PODC'15], we improve the number of interactions by almost a linear factor.Furthermore, our protocols can be made uniform (working correctly without anyinformation on the population size $n$), yielding the first uniform majorityprotocols that stabilize in a subquadratic number of interactions.

Time-space Trade-offs in Population Protocols for the Majority Problem