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DOI: 10.4230/LIPIcs.ESA.2017.48
URN: urn:nbn:de:0030-drops-78749
URL: https://drops.dagstuhl.de/opus/volltexte/2017/7874/
Henzinger, Monika ; Leniowski, Dariusz ; Mathieu, Claire
Dynamic Clustering to Minimize the Sum of Radii
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Abstract
In this paper, we study the problem of opening centers to cluster a set of clients in a metric space so as to minimize the sum of the costs of the centers and of the cluster radii, in a dynamic environment where clients arrive and depart, and the solution must be updated efficiently while remaining competitive with respect to the current optimal solution. We call this dynamic sum-of-radii clustering problem. We present a data structure that maintains a solution whose cost is within a constant factor of the cost of an optimal solution in metric spaces with bounded doubling dimension and whose worst-case update time is logarithmic in the parameters of the problem.
BibTeX - Entry
@InProceedings{henzinger_et_al:LIPIcs:2017:7874,
author = {Monika Henzinger and Dariusz Leniowski and Claire Mathieu},
title = {{Dynamic Clustering to Minimize the Sum of Radii}},
booktitle = {25th Annual European Symposium on Algorithms (ESA 2017)},
pages = {48:1--48:10},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-049-1},
ISSN = {1868-8969},
year = {2017},
volume = {87},
editor = {Kirk Pruhs and Christian Sohler},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2017/7874},
URN = {urn:nbn:de:0030-drops-78749},
doi = {10.4230/LIPIcs.ESA.2017.48},
annote = {Keywords: dynamic algorithm, clustering, approximation, doubling dimension}
}
| Keywords: | dynamic algorithm, clustering, approximation, doubling dimension | |
| Seminar: | 25th Annual European Symposium on Algorithms (ESA 2017) | |
| Issue date: | 2017 | |
| Date of publication: | 01.09.2017 |
