Time-Space Trade-offs in Population Protocols

Population protocols [AAD+ 06] are a popular model of distributed computing, in which randomlyinteracting agents with little computational power cooperate to jointly perform computational tasks. Recent work has focused on the complexity of fundamental tasks in the population model, such as leader election (which requires convergence to a single agent in a special ‘’leader” state), and majority (in which agents must converge to a decision as to which of two possible initial states had higher initial count). Known upper and lower bounds point towards an inherent trade-off between the time complexity of these protocols, and the space complexity, i.e. size of the memory available to each agent. In this paper, we explore this trade-off and provide new upper and lower bounds for these two fundamental tasks. First, we prove a new unified lower bound, which relates the space available per node with the time complexity achievable by the protocol: for instance, our result implies that an...

• Type: Journal
• Year: 2016
• Where: CORR
• Authors: Dan Alistarh, James Aspnes, David Eisenstat, Rati Gelashvili, Ronald L. Rivest
• Keywords: CORR 2016, Education