LIPIcs.DISC.2020.40.pdf
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Brief Announcement: Efficient Load-Balancing Through Distributed Token Dropping
Authors
Sebastian Brandt 
,
Barbara Keller ,
Joel Rybicki ,
Jukka Suomela ,
Jara Uitto
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Volume:
34th International Symposium on Distributed Computing (DISC 2020)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: International Symposium on Distributed Computing (DISC) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2020-10-07
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Sebastian Brandt, Barbara Keller, Joel Rybicki, Jukka Suomela, and Jara Uitto. Brief Announcement: Efficient Load-Balancing Through Distributed Token Dropping. In 34th International Symposium on Distributed Computing (DISC 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 179, pp. 40:1-40:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.DISC.2020.40
Abstract
We introduce a new graph problem, the token dropping game, and we show how to solve it efficiently in a distributed setting. We use the token dropping game as a tool to design an efficient distributed algorithm for the stable orientation problem, which is a special case of the more general locally optimal semi-matching problem. The prior work by Czygrinow et al. (DISC 2012) finds a locally optimal semi-matching in O(Δ⁵) rounds in graphs of maximum degree Δ, which directly implies an algorithm with the same runtime for stable orientations. We improve the runtime to O(Δ⁴) for stable orientations and prove a lower bound of Ω(Δ) rounds.
Subject Classification
ACM Subject Classification
- Theory of computation → Distributed algorithms
Keywords
- distributed algorithms
- graph problems
- semi-matching
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References
- Matti Åstrand and Jukka Suomela. Fast distributed approximation algorithms for vertex cover and set cover in anonymous networks. In SPAA, 2010. URL: https://doi.org/10.1145/1810479.1810533.
- Alkida Balliu, Sebastian Brandt, Juho Hirvonen, Dennis Olivetti, Mikaël Rabie, and Jukka Suomela. Lower Bounds for Maximal Matchings and Maximal Independent Sets. In FOCS, 2019. URL: https://doi.org/10.1109/FOCS.2019.00037.
- Sebastian Brandt. An Automatic Speedup Theorem for Distributed Problems. In PODC, 2019. URL: https://doi.org/10.1145/3293611.3331611.
- Andrzej Czygrinow, Michal Hanćkowiak, Edyta Szymańska, and Wojciech Wawrzyniak. Distributed 2-Approximation Algorithm for the Semi-matching Problem. In DISC, 2012. URL: https://doi.org/10.1007/978-3-642-33651-5_15.
- Mika Göös, Juho Hirvonen, and Jukka Suomela. Linear-in-Δ lower bounds in the LOCAL model. Distributed Computing, 30(5), 2017. URL: https://doi.org/10.1007/s00446-015-0245-8.
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Michal Hanckowiak, Michal Karonski, and Alessandro Panconesi. On the Distributed Complexity of Computing Maximal Matchings. In SODA, 1998.
- Nathan Linial. Locality in Distributed Graph Algorithms. SIAM J. Comput., 21(1), 1992. URL: https://doi.org/10.1137/0221015.
- Moni Naor and Larry Stockmeyer. What Can be Computed Locally? SIAM J. Comput., 24(6), 1995. URL: https://doi.org/10.1137/S0097539793254571.