DocumentCode
2959950
Title
Self-organizing Particle Systems
Author
Drees, Maximilian ; Hüllmann, Martina ; Koutsopoulos, Andreas ; Scheideler, Christian
fYear
2012
fDate
21-25 May 2012
Firstpage
1272
Lastpage
1283
Abstract
Nanoparticles are getting more and more in the focus of the scientific community since the potential for the development of very small particles interacting with each other and completing medical and other tasks is getting bigger year by year. In this work we introduce a distributed local algorithm for arranging a set of nanoparticles on the discrete plane into specific geometric shapes, for instance a rectangle. The concept of a particle we use can be seen as a simple mobile robot with the following restrictions: it can only view the state of robots it is physically connected to, is anonymous, has only a constant size memory, can only move by using other particles as an anchor point on which it pulls itself alongside, and it operates in Look-Compute-Move cycles. The main result of this work is the presentation of a random distributed local algorithm which transforms any given connected set of particles into a particular geometric shape. As an example we provide a version of this algorithm for forming a rectangle with an arbitrary predefined aspect ratio. To the best of our knowledge this is the first work that considers arrangement problems for these types of robots.
Keywords
distributed algorithms; mobile robots; nanoparticles; random processes; self-adjusting systems; constant size memory; discrete plane; geometric shapes; look-compute-move cycles; mobile robot; nanoparticles; random distributed local algorithm; self-organizing particle systems; Computer science; Connectors; Nanoparticles; Robot kinematics; Robot sensing systems; Shape; distributed local algorithm; mobile robots; particles; self-organization;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel & Distributed Processing Symposium (IPDPS), 2012 IEEE 26th International
Conference_Location
Shanghai
ISSN
1530-2075
Print_ISBN
978-1-4673-0975-2
Type
conf
DOI
10.1109/IPDPS.2012.116
Filename
6267929
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