3 Search Results for "Martins, Luis Carlos"

Document
DOI: 10.4230/LIPIcs.ECRTS.2025.3
Enabling Containerisation of Distributed Applications with Real-Time Constraints

Authors: Nasim Samimi, Luca Abeni, Daniel Casini, Mauro Marinoni, Twan Basten, Mitra Nasri, Marc Geilen, and Alessandro Biondi

Published in: LIPIcs, Volume 335, 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)

Abstract
Containerisation is becoming a cornerstone of modern distributed systems, thanks to their lightweight virtualisation, high portability, and seamless integration with orchestration tools such as Kubernetes. The usage of containers has also gained traction in real-time cyber-physical systems, such as software-defined vehicles, which are characterised by strict timing requirements to ensure safety and performance. Nevertheless, ensuring real-time execution of co-located containers is challenging because of mutual interference due to the sharing of the same processing hardware. Existing parallel computing frameworks such as Ray and its Kubernetes-enabled variant, KubeRay, excel in distributed computation but lack support for scheduling policies that allow guaranteeing real-time timing constraints and CPU resource isolation between containers, such as the SCHED_DEADLINE policy of Linux. To fill this gap, this paper extends Ray to support real-time containers that leverage SCHED_DEADLINE. To this end, we propose KubeDeadline, a novel, modular Kubernetes extension to support SCHED_DEADLINE. We evaluate our approach through extensive experiments, using synthetic workloads and a case study based on the MobileNet and EfficientNet deep neural networks. Our evaluation shows that KubeDeadline ensures deadline compliance in all synthetic workloads, adds minimal deployment overhead (in the order of milliseconds), and achieves lower worst-case response times, up to 4 times lower, than vanilla Kubernetes under background interference.
Cite as

Nasim Samimi, Luca Abeni, Daniel Casini, Mauro Marinoni, Twan Basten, Mitra Nasri, Marc Geilen, and Alessandro Biondi. Enabling Containerisation of Distributed Applications with Real-Time Constraints. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 3:1-3:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{samimi_et_al:LIPIcs.ECRTS.2025.3,
  author =	{Samimi, Nasim and Abeni, Luca and Casini, Daniel and Marinoni, Mauro and Basten, Twan and Nasri, Mitra and Geilen, Marc and Biondi, Alessandro},
  title =	{{Enabling Containerisation of Distributed Applications with Real-Time Constraints}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{3:1--3:29},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-377-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{335},
  editor =	{Mancuso, Renato},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2025.3},
  URN =		{urn:nbn:de:0030-drops-235816},
  doi =		{10.4230/LIPIcs.ECRTS.2025.3},
  annote =	{Keywords: Kubernetes, real-time containers, SCHED\underlineDEADLINE, KubeRay}
}
Document
Survey
DOI: 10.4230/TGDK.3.1.3
Uncertainty Management in the Construction of Knowledge Graphs: A Survey

Authors: Lucas Jarnac, Yoan Chabot, and Miguel Couceiro

Published in: TGDK, Volume 3, Issue 1 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 1

Abstract
Knowledge Graphs (KGs) are a major asset for companies thanks to their great flexibility in data representation and their numerous applications, e.g., vocabulary sharing, Q&A or recommendation systems. To build a KG, it is a common practice to rely on automatic methods for extracting knowledge from various heterogeneous sources. However, in a noisy and uncertain world, knowledge may not be reliable and conflicts between data sources may occur. Integrating unreliable data would directly impact the use of the KG, therefore such conflicts must be resolved. This could be done manually by selecting the best data to integrate. This first approach is highly accurate, but costly and time-consuming. That is why recent efforts focus on automatic approaches, which represent a challenging task since it requires handling the uncertainty of extracted knowledge throughout its integration into the KG. We survey state-of-the-art approaches in this direction and present constructions of both open and enterprise KGs. We then describe different knowledge extraction methods and discuss downstream tasks after knowledge acquisition, including KG completion using embedding models, knowledge alignment, and knowledge fusion in order to address the problem of knowledge uncertainty in KG construction. We conclude with a discussion on the remaining challenges and perspectives when constructing a KG taking into account uncertainty.
Cite as

Lucas Jarnac, Yoan Chabot, and Miguel Couceiro. Uncertainty Management in the Construction of Knowledge Graphs: A Survey. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 1, pp. 3:1-3:48, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{jarnac_et_al:TGDK.3.1.3,
  author =	{Jarnac, Lucas and Chabot, Yoan and Couceiro, Miguel},
  title =	{{Uncertainty Management in the Construction of Knowledge Graphs: A Survey}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:48},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.1.3},
  URN =		{urn:nbn:de:0030-drops-233733},
  doi =		{10.4230/TGDK.3.1.3},
  annote =	{Keywords: Knowledge reconciliation, Uncertainty, Heterogeneous sources, Knowledge graph construction}
}
Document
DOI: 10.4230/OASIcs.ICPEC.2023.3
LCSMAR, an AR Based Tool to Inspect Imperative Programs

Authors: Luis Carlos Martins, Lázaro Vinicius Lima, and Pedro Rangel Henriques

Published in: OASIcs, Volume 112, 4th International Computer Programming Education Conference (ICPEC 2023)

Abstract
LCSMAR is a Learning Resource that takes advantage of Augmented Reality in order to promote the development of Computational Thinking among students who are starting to dive in to the world of computer programming. Students can write code in a imperative programming language and, with the help of their mobile phone, they can visualize and analyze the execution of the code they developed, seeing how variable and data structures change over time with each instruction. Augmented Reality tools allow the visualization of abstract concepts that are often misunderstood and that cause misconception among students, which in term should help students develop the abilities to understand and use these abstract concepts, such as data structures, in other areas of application.
Cite as

Luis Carlos Martins, Lázaro Vinicius Lima, and Pedro Rangel Henriques. LCSMAR, an AR Based Tool to Inspect Imperative Programs. In 4th International Computer Programming Education Conference (ICPEC 2023). Open Access Series in Informatics (OASIcs), Volume 112, pp. 3:1-3:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{martins_et_al:OASIcs.ICPEC.2023.3,
  author =	{Martins, Luis Carlos and Lima, L\'{a}zaro Vinicius and Henriques, Pedro Rangel},
  title =	{{LCSMAR, an AR Based Tool to Inspect Imperative Programs}},
  booktitle =	{4th International Computer Programming Education Conference (ICPEC 2023)},
  pages =	{3:1--3:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-290-7},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{112},
  editor =	{Peixoto de Queir\'{o}s, Ricardo Alexandre and Teixeira Pinto, M\'{a}rio Paulo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2023.3},
  URN =		{urn:nbn:de:0030-drops-184994},
  doi =		{10.4230/OASIcs.ICPEC.2023.3},
  annote =	{Keywords: Augmented Reality, Learning Resources, Computer Programming, Computational Thinking}
}
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