License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CP.2021.60
URN: urn:nbn:de:0030-drops-153518
URL: https://drops.dagstuhl.de/opus/volltexte/2021/15351/
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Zivan, Roie ; Perry, Omer ; Rachmut, Ben ; Yeoh, William

The Effect of Asynchronous Execution and Message Latency on Max-Sum

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LIPIcs-CP-2021-60.pdf (1 MB)


Abstract

Max-sum is a version of belief propagation that was adapted for solving distributed constraint optimization problems (DCOPs). It has been studied theoretically and empirically, extended to versions that improve solution quality and converge rapidly, and is applicable to multiple distributed applications. The algorithm was presented both as a synchronous and an asynchronous algorithm, however, neither the differences in the performance of these two execution versions nor the implications of message latency on the two versions have been investigated to the best of our knowledge.
We contribute to the body of knowledge on Max-sum by: (1) Establishing the theoretical differences between the two execution versions of the algorithm, focusing on the construction of beliefs; (2) Empirically evaluating the differences between the solutions generated by the two versions of the algorithm, with and without message latency; and (3) Establishing both theoretically and empirically the positive effect of damping on reducing the differences between the two versions. Our results indicate that in contrast to recent published results indicating the drastic effect that message latency has on distributed local search, damped Max-sum is robust to message latency.

BibTeX - Entry

@InProceedings{zivan_et_al:LIPIcs.CP.2021.60,
  author =	{Zivan, Roie and Perry, Omer and Rachmut, Ben and Yeoh, William},
  title =	{{The Effect of Asynchronous Execution and Message Latency on Max-Sum}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{60:1--60:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/15351},
  URN =		{urn:nbn:de:0030-drops-153518},
  doi =		{10.4230/LIPIcs.CP.2021.60},
  annote =	{Keywords: Distributed constraints, Distributed problem solving}
}

Keywords: Distributed constraints, Distributed problem solving
Collection: 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)
Issue Date: 2021
Date of publication: 15.10.2021


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