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Documents authored by Talbot, Pierre

Document
DOI: 10.4230/LIPIcs.CP.2023.34
Constraint Programming with External Worst-Case Traversal Time Analysis

Authors: Pierre Talbot, Tingting Hu, and Nicolas Navet

Published in: LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)

Abstract
The allocation of software functions to processors under compute capacity and network links constraints is an important optimization problem in the field of embedded distributed systems. We present a hybrid approach to solve the allocation problem combining a constraint solver and a worst-case traversal time (WCTT) analysis that verifies the network timing constraints. The WCTT analysis is implemented as an industrial black-box program, which makes a tight integration with constraint solving challenging. We contribute to a new multi-objective constraint solving algorithm for integrating external under-approximating functions, such as the WCTT analysis, with constraint solving, and prove its correctness. We apply this new algorithm to the allocation problem in the context of automotive service-oriented architectures based on Ethernet networks, and provide a new dataset of realistic instances to evaluate our approach.
Cite as

Pierre Talbot, Tingting Hu, and Nicolas Navet. Constraint Programming with External Worst-Case Traversal Time Analysis. In 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 280, pp. 34:1-34:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{talbot_et_al:LIPIcs.CP.2023.34,
  author =	{Talbot, Pierre and Hu, Tingting and Navet, Nicolas},
  title =	{{Constraint Programming with External Worst-Case Traversal Time Analysis}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{34:1--34:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.34},
  URN =		{urn:nbn:de:0030-drops-190713},
  doi =		{10.4230/LIPIcs.CP.2023.34},
  annote =	{Keywords: Constraint programming, external function, multi-objective optimization, network analysis, worst-case traversal time analysis, abstract interpretation}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.CP.2023.44
Constraint Model for the Satellite Image Mosaic Selection Problem (Short Paper)

Authors: Manuel Combarro Simón, Pierre Talbot, Grégoire Danoy, Jedrzej Musial, Mohammed Alswaitti, and Pascal Bouvry

Published in: LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)

Abstract
Satellite imagery solutions are widely used to study and monitor different regions of the Earth. However, a single satellite image can cover only a limited area. In cases where a larger area of interest is studied, several images must be stitched together to create a single larger image, called a mosaic, that can cover the area. Today, with the increasing number of satellite images available for commercial use, selecting the images to build the mosaic is challenging, especially when the user wants to optimize one or more parameters, such as the total cost and the cloud coverage percentage in the mosaic. More precisely, for this problem the input is an area of interest, several satellite images intersecting the area, a list of requirements relative to the image and the mosaic, such as cloud coverage percentage, image resolution, and a list of objectives to optimize. We contribute to the constraint and mixed integer lineal programming formulation of this new problem, which we call the satellite image mosaic selection problem, which is a multi-objective extension of the polygon cover problem. We propose a dataset of realistic and challenging instances, where the images were captured by the satellite constellations SPOT, Pléiades and Pléiades Neo. We evaluate and compare the two proposed models and show their efficiency for large instances, up to 200 images.
Cite as

Manuel Combarro Simón, Pierre Talbot, Grégoire Danoy, Jedrzej Musial, Mohammed Alswaitti, and Pascal Bouvry. Constraint Model for the Satellite Image Mosaic Selection Problem (Short Paper). In 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 280, pp. 44:1-44:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{combarrosimon_et_al:LIPIcs.CP.2023.44,
  author =	{Combarro Sim\'{o}n, Manuel and Talbot, Pierre and Danoy, Gr\'{e}goire and Musial, Jedrzej and Alswaitti, Mohammed and Bouvry, Pascal},
  title =	{{Constraint Model for the Satellite Image Mosaic Selection Problem}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{44:1--44:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.44},
  URN =		{urn:nbn:de:0030-drops-190815},
  doi =		{10.4230/LIPIcs.CP.2023.44},
  annote =	{Keywords: constraint modeling, satellite imaging, set covering, polygon covering}
}
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