Coordinating Amoebots via Reconfigurable Circuits

Michael Feldmann, Andreas Padalkin, Christian Scheideler, Shlomi Dolev

Research output: Contribution to journalArticlepeer-review

Abstract

We consider an extension to the geometric amoebot model that allows amoebots to form so-called circuits. Given a connected amoebot structure, a circuit is a subgraph formed by the amoebots that permits the instant transmission of signals. We show that such an extension allows for significantly faster solutions to a variety of problems related to programmable matter. More specifically, we provide algorithms for leader election, consensus, compass alignment, chirality agreement, and shape recognition. Leader election can be solved in Θ(logn) rounds, with high probability (w.h.p.), consensus in O(1) rounds, and both, compass alignment and chirality agreement, can be solved in O(logn) rounds, w.h.p. For shape recognition, the amoebots have to decide whether the amoebot structure forms a particular shape. We show that the amoebots can detect a shape composed of triangles within O(1) rounds. Finally, we show how the amoebots can detect a parallelogram with linear and polynomial side ratio within Θ(logn) rounds, w.h.p.

Original languageEnglish
Pages (from-to)317-343
Number of pages27
JournalJournal of Computational Biology
Volume29
Issue number4
DOIs
StatePublished - 1 Apr 2022

Keywords

  • amoebot model
  • distributed consensus
  • leader election
  • programmable matter
  • reconfigurable circuits
  • shape recognition

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics

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