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When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.DISC.2017.8
URN: urn:nbn:de:0030-drops-79631
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2017/7963/
Bouchard, Sébastien ;
Bournat, Marjorie ;
Dieudonné, Yoann ;
Dubois, Swan ;
Petit, Franck
Asynchronous Approach in the Plane: A Deterministic Polynomial Algorithm
Abstract
In this paper we study the task of approach of two mobile agents having the same limited range of vision and moving asynchronously in the plane. This task consists in getting them in finite time within each other's range of vision. The agents execute the same deterministic algorithm and are assumed to have a compass showing the cardinal directions as well as a unit measure. On the other hand, they do not share any global coordinates system (like GPS), cannot communicate and have distinct labels. Each agent knows its label but does not know the label of the other agent or the initial position of the other agent relative to its own. The route of an agent is a sequence of segments that are subsequently traversed in order to achieve approach. For each agent, the computation of its route depends only on its algorithm and its label. An adversary chooses the initial positions of both agents in the plane and controls the way each of them moves along every segment of the routes, in particular by arbitrarily varying the speeds of the agents. Roughly speaking, the goal of the adversary is to prevent the agents from solving the task, or at least to ensure that the agents have covered as much distance as possible before seeing each other. A deterministic approach algorithm is a deterministic algorithm that always allows two agents with any distinct labels to solve the task of approach regardless of the choices and the behavior of the adversary. The cost of a complete execution of an approach algorithm is the length of both parts of route travelled by the agents until approach is completed.
Let Delta and l be the initial distance separating the agents and the length of (the binary representation of) the shortest label, respectively. Assuming that Delta and l are unknown to both agents, does there exist a deterministic approach algorithm whose cost is polynomial in Delta and l?
Actually the problem of approach in the plane reduces to the network problem of rendezvous in an infinite oriented grid, which consists in ensuring that both agents end up meeting at the same time at a node or on an edge of the grid. By designing such a rendezvous algorithm with appropriate properties, as we do in this paper, we provide a positive answer to the above question.
Our result turns out to be an important step forward from a computational point of view, as the other algorithms allowing to solve the same problem either have an exponential cost in the initial separating distance and in the labels of the agents, or require each agent to know its starting position in a global system of coordinates, or only work under a much less powerful adversary.
BibTeX - Entry
@InProceedings{bouchard_et_al:LIPIcs:2017:7963,
author = {S{\'e}bastien Bouchard and Marjorie Bournat and Yoann Dieudonn{\'e} and Swan Dubois and Franck Petit},
title = {{Asynchronous Approach in the Plane: A Deterministic Polynomial Algorithm}},
booktitle = {31st International Symposium on Distributed Computing (DISC 2017)},
pages = {8:1--8:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-053-8},
ISSN = {1868-8969},
year = {2017},
volume = {91},
editor = {Andr{\'e}a W. Richa},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2017/7963},
URN = {urn:nbn:de:0030-drops-79631},
doi = {10.4230/LIPIcs.DISC.2017.8},
annote = {Keywords: mobile agents, asynchronous rendezvous, plane, infinite grid, deterministic algorithm, polynomial cost}
}
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Keywords: |
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mobile agents, asynchronous rendezvous, plane, infinite grid, deterministic algorithm, polynomial cost |
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Collection: |
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31st International Symposium on Distributed Computing (DISC 2017) |
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Issue Date: |
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2017 |
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Date of publication: |
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12.10.2017 |
