3 Search Results for "Ramírez, Sergio"

Document
DOI: 10.4230/LIPIcs.ECRTS.2025.4
A Multi-UAV Router and Scheduler for Executing Spatially Scattered Real-Time Tasks

Authors: Sreyashi Mukherjee, Sachin Yadav, Yedla Anil Kumar, and Arnab Sarkar

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

Abstract
Cyber-Physical Systems (CPSs) operating in remote or field scenarios often face limited local processing capacity, necessitating complex real-time monitoring and control via remote processing through mobile edge networks, satellite systems, or UAVs. With recent advancements, UAVs are increasingly being favored for such applications, particularly in isolated areas beyond edge or satellite network coverage. This paper presents a unified UAV scheduling and routing framework for executing geographically distributed real-time CPS tasks under both periodic and aperiodic arrival models. We address the challenge of minimizing the number of UAVs required while ensuring strict adherence to task deadlines across diverse temporal and spatial settings. At first, we propose an efficient heuristic strategy called UAV Scheduling and Routing Algorithm for Real-time Tasks - Periodic Arrivals (USRART-P), which decomposes applications into task instances and sequentially creates per-UAV routes and schedules within a hyperperiod, maximizing the number of task instances each UAV can cover while meeting deadlines. Adapting to this framework, we develop two additional variants to handle aperiodic CPS tasks: USRART-SA for Synchronous Aperiodic Arrivals (common arrival time, distinct deadlines) and USRART-AA for Asynchronous Aperiodic Arrivals (distinct but known arrival times and deadlines). For the case of periodic tasks, we frame the problem as a constraint optimization formulation which aims to minimize the number of UAVs that are required to generate static hyperperiodic travel routes with task execution schedules for all UAVs, and discuss how the formulation can be adapted for aperiodic tasks. Solution to this formulation using standard off-the-shelf solvers achieves optimality but incurs high computational overheads. Through extensive simulations, we show that USRART exhibits high performance across diverse operational scenarios, varying task distributions, execution demands, and spatial layouts. The results emphasize USRART’s flexibility and effectiveness in real-world UAV-based CPS scenarios, especially in environments with limited resources and infrastructure.
Cite as

Sreyashi Mukherjee, Sachin Yadav, Yedla Anil Kumar, and Arnab Sarkar. A Multi-UAV Router and Scheduler for Executing Spatially Scattered Real-Time Tasks. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 4:1-4:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{mukherjee_et_al:LIPIcs.ECRTS.2025.4,
  author =	{Mukherjee, Sreyashi and Yadav, Sachin and Kumar, Yedla Anil and Sarkar, Arnab},
  title =	{{A Multi-UAV Router and Scheduler for Executing Spatially Scattered Real-Time Tasks}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{4:1--4:25},
  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.2025.4},
  URN =		{urn:nbn:de:0030-drops-235822},
  doi =		{10.4230/LIPIcs.ECRTS.2025.4},
  annote =	{Keywords: UAV Scheduling, Task Allocation, Optimization, Execution Time}
}
Document
Position
DOI: 10.4230/TGDK.1.1.5
Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities

Authors: Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they produce and consume vast amounts of scientific data, much of which is intrinsically relational and graph-structured. The volume of data and the complexity of scientific concepts and relations referred to therein promote the application of advanced knowledge-driven technologies for managing and interpreting data, with the ultimate aim to advance scientific discovery. In this survey and position paper, we discuss recent developments and advances in the use of graph-based technologies in life sciences and set out a vision for how these technologies will impact these fields into the future. We focus on three broad topics: the construction and management of Knowledge Graphs (KGs), the use of KGs and associated technologies in the discovery of new knowledge, and the use of KGs in artificial intelligence applications to support explanations (explainable AI). We select a few exemplary use cases for each topic, discuss the challenges and open research questions within these topics, and conclude with a perspective and outlook that summarizes the overarching challenges and their potential solutions as a guide for future research.
Cite as

Jiaoyan Chen, Hang Dong, Janna Hastings, Ernesto Jiménez-Ruiz, Vanessa López, Pierre Monnin, Catia Pesquita, Petr Škoda, and Valentina Tamma. Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 5:1-5:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{chen_et_al:TGDK.1.1.5,
  author =	{Chen, Jiaoyan and Dong, Hang and Hastings, Janna and Jim\'{e}nez-Ruiz, Ernesto and L\'{o}pez, Vanessa and Monnin, Pierre and Pesquita, Catia and \v{S}koda, Petr and Tamma, Valentina},
  title =	{{Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:33},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.5},
  URN =		{urn:nbn:de:0030-drops-194791},
  doi =		{10.4230/TGDK.1.1.5},
  annote =	{Keywords: Knowledge graphs, Life science, Knowledge discovery, Explainable AI}
}
Document
DOI: 10.4230/LIPIcs.CONCUR.2019.29
Reasoning About Distributed Knowledge of Groups with Infinitely Many Agents

Authors: Michell Guzmán, Sophia Knight, Santiago Quintero, Sergio Ramírez, Camilo Rueda, and Frank Valencia

Published in: LIPIcs, Volume 140, 30th International Conference on Concurrency Theory (CONCUR 2019)

Abstract
Spatial constraint systems (scs) are semantic structures for reasoning about spatial and epistemic information in concurrent systems. We develop the theory of scs to reason about the distributed information of potentially infinite groups. We characterize the notion of distributed information of a group of agents as the infimum of the set of join-preserving functions that represent the spaces of the agents in the group. We provide an alternative characterization of this notion as the greatest family of join-preserving functions that satisfy certain basic properties. We show compositionality results for these characterizations and conditions under which information that can be obtained by an infinite group can also be obtained by a finite group. Finally, we provide algorithms that compute the distributive group information of finite groups.
Cite as

Michell Guzmán, Sophia Knight, Santiago Quintero, Sergio Ramírez, Camilo Rueda, and Frank Valencia. Reasoning About Distributed Knowledge of Groups with Infinitely Many Agents. In 30th International Conference on Concurrency Theory (CONCUR 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 140, pp. 29:1-29:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{guzman_et_al:LIPIcs.CONCUR.2019.29,
  author =	{Guzm\'{a}n, Michell and Knight, Sophia and Quintero, Santiago and Ram{\'\i}rez, Sergio and Rueda, Camilo and Valencia, Frank},
  title =	{{Reasoning About Distributed Knowledge of Groups with Infinitely Many Agents}},
  booktitle =	{30th International Conference on Concurrency Theory (CONCUR 2019)},
  pages =	{29:1--29:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-121-4},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{140},
  editor =	{Fokkink, Wan and van Glabbeek, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2019.29},
  URN =		{urn:nbn:de:0030-drops-109314},
  doi =		{10.4230/LIPIcs.CONCUR.2019.29},
  annote =	{Keywords: Reasoning about Groups, Distributed Knowledge, Infinitely Many Agents, Reasoning about Space, Algebraic Modeling}
}
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