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Leader Election and Shape Formation with Self-organizing Programmable Matter

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DNA Computing and Molecular Programming (DNA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9211))

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Abstract

In this paper we consider programmable matter consisting of simple computational elements, called particles, that can establish and release bonds and can actively move in a self-organized way, and we investigate the feasibility of solving fundamental problems relevant for programmable matter. As a model for such self-organizing particle systems, we will use a generalization of the geometric amoebot model first proposed in [21]. Based on the geometric model, we present efficient local-control algorithms for leader election and line formation requiring only particles with constant size memory, and we also discuss the limitations of solving these problems within the general amoebot model.

Z. Derakhshandeh and A.W. Richa—Supported in part by the NSF under Awards CCF-1353089 and CCF-1422603.

R. Gmyr, T. Strothmann and C. Scheideler—Supported in part by DFG grant SCHE 1592/3-1.

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Notes

  1. 1.

    For a simulation video of the Line Formation Algorithm please see http://sops.cs.upb.de.

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Authors and Affiliations

  1. Computer Science, CIDSE, Arizona State University, Tempe, USA

    Zahra Derakhshandeh, Rida Bazzi & Andréa W. Richa

  2. Department of Computer Science, University of Paderborn, Paderborn, Germany

    Robert Gmyr, Thim Strothmann & Christian Scheideler

Authors
  1. Zahra Derakhshandeh
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  2. Robert Gmyr
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  3. Thim Strothmann
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  4. Rida Bazzi
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  5. Andréa W. Richa
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  6. Christian Scheideler
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Corresponding author

Correspondence to Thim Strothmann .

Editor information

Editors and Affiliations

  1. Microsoft Research, Cambridge, United Kingdom

    Andrew Phillips

  2. Wyss Institute, Boston, Massachusetts, USA

    Peng Yin

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Derakhshandeh, Z., Gmyr, R., Strothmann, T., Bazzi, R., Richa, A.W., Scheideler, C. (2015). Leader Election and Shape Formation with Self-organizing Programmable Matter. In: Phillips, A., Yin, P. (eds) DNA Computing and Molecular Programming. DNA 2015. Lecture Notes in Computer Science(), vol 9211. Springer, Cham. https://doi.org/10.1007/978-3-319-21999-8_8

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  • DOI: https://doi.org/10.1007/978-3-319-21999-8_8

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