Improved leader election for self-organizing programmable matter

Joshua J. Daymude, Robert Gmyr, Andrea Richa, Christian Scheideler, Thim Strothmann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

We consider programmable matter that consists of computationally limited devices (called particles) that are able to self-organize in order to achieve some collective goal without the need for central control or external intervention. We use the geometric amoebot model to describe such self-organizing particle systems, which defines how particles can actively move and communicate with one another. In this paper, we present an efficient local-control algorithm which solves the leader election problem in O(n) asynchronous rounds with high probability, where n is the number of particles in the system. Our algorithm relies only on local information — particles do not have unique identifiers, any knowledge of n, or any sort of global coordinate system — and requires only constant memory per particle.

Original languageEnglish (US)
Title of host publicationAlgorithms for Sensor Systems - 13th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS 2017, Revised Selected Papers
PublisherSpringer Verlag
Pages127-140
Number of pages14
Volume10718 LNCS
ISBN (Print)9783319727509
DOIs
Publication statusPublished - Jan 1 2017
Event13th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS 2017 - Vienna, Austria
Duration: Sep 4 2017Sep 8 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10718 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS 2017
CountryAustria
CityVienna
Period9/4/179/8/17

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Daymude, J. J., Gmyr, R., Richa, A., Scheideler, C., & Strothmann, T. (2017). Improved leader election for self-organizing programmable matter. In Algorithms for Sensor Systems - 13th International Symposium on Algorithms and Experiments for Wireless Sensor Networks, ALGOSENSORS 2017, Revised Selected Papers (Vol. 10718 LNCS, pp. 127-140). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10718 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-72751-6_10