Efficient Assignment of Identities in Anonymous Populations
Leszek Gasieniec, Jesper Jansson, Christos Levcopoulos, and Andrzej, Lingas

TL;DR
This paper introduces efficient protocols for assigning unique labels to agents in population protocols, optimizing for speed, state complexity, and safety, with theoretical bounds and trade-offs analyzed.
Contribution
It presents new silent, safe labeling protocols with asymptotically optimal interaction counts and explores the trade-offs between states and interactions in population protocols.
Findings
Fast silent labeling protocol with $O(n \, \log n/\epsilon)$ interactions.
Lower bounds on interactions for pool labeling protocols.
A nearly optimal protocol with $n+5\sqrt{n}$ states and $O(n^3)$ interactions.
Abstract
We consider the fundamental problem of assigning distinct labels to agents in the probabilistic model of population protocols. Our protocols operate under the assumption that the size of the population is embedded in the transition function. Our labeling protocols are silent w.h.p., i.e., eventually each agent reaches its final state and remains in it forever w.h.p., as well as safe, i.e., never update the label assigned to any single agent. We first present a fast, silent w.h.p.and safe labeling protocol for which the required number of interactions is asymptotically optimal, i.e., w.h.p. It uses states, for any and the label range Furthermore, we consider the so-called pool labeling protocols that include our fast protocol. We show that the expected number of interactions required by any pool protocol is…
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Taxonomy
TopicsDistributed systems and fault tolerance · Advanced Database Systems and Queries · Machine Learning and Algorithms
