Consider a set of n mobile computational entities, called robots, located and operating on a continuous cycle C (e.g., the perimeter of a closed region of R^2) of arbitrary length l. The robots are identical, can only see their current location, have no location awareness, and cannot communicate at a distance. In this weak setting, we study the classical problems of gathering (GATHER), requiring all robots to meet at a same location; and election (ELECT), requiring all robots to agree on a single one as the "leader". We investigate how to solve the problems depending on the amount of knowledge (exact, upper bound, none) the robots have about their number n and about the length of the cycle l. Cost of the algorithms is analyzed with respect to time and number of random bits. We establish a variety of new results specific to the continuous cycle - a geometric domain never explored before for GATHER and ELECT in a mobile robot setting; compare Monte Carlo and Las Vegas algorithms; and obtain several optimal bounds.
@InProceedings{flocchini_et_al:LIPIcs.ISAAC.2019.8, author = {Flocchini, Paola and Killick, Ryan and Kranakis, Evangelos and Santoro, Nicola and Yamashita, Masafumi}, title = {{Gathering and Election by Mobile Robots in a Continuous Cycle}}, booktitle = {30th International Symposium on Algorithms and Computation (ISAAC 2019)}, pages = {8:1--8:19}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-130-6}, ISSN = {1868-8969}, year = {2019}, volume = {149}, editor = {Lu, Pinyan and Zhang, Guochuan}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2019.8}, URN = {urn:nbn:de:0030-drops-115044}, doi = {10.4230/LIPIcs.ISAAC.2019.8}, annote = {Keywords: Cycle, Election, Gathering, Las Vegas, Monte Carlo, Randomized Algorithm} }
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