Search Results

Documents authored by Chantem, Thidapat

Document
DOI: 10.4230/LITES.10.1.3
Limited-Preemption EDF Scheduling for Multi-Phase Secure Tasks

Authors: Benjamin Standaert, Fatima Raadia, Marion Sudvarg, Sanjoy Baruah, Thidapat Chantem, Nathan Fisher, and Christopher Gill

Published in: LITES, Volume 10, Issue 1 (2025). Leibniz Transactions on Embedded Systems, Volume 10, Issue 1

Abstract
Safety-critical embedded systems such as autonomous vehicles typically have only very limited computational capabilities on board that must be carefully managed to provide required enhanced functionalities. As these systems become more complex and inter-connected, some parts may need to be secured to prevent unauthorized access, or isolated to ensure correctness. We propose the multi-phase secure (MPS) task model as a natural extension of the widely used sporadic task model for modeling both the timing and the security (and isolation) requirements for such systems. Under MPS, task phases reflect execution using different security mechanisms which each have associated execution time costs for startup and teardown. We develop corresponding limited-preemption EDF scheduling algorithms and associated pseudo-polynomial schedulability tests for constrained-deadline MPS tasks. In doing so, we provide a correction to a long-standing schedulability condition for EDF under limited-preemption. Evaluation shows that the proposed tests are efficient to compute for bounded utilizations. We empirically demonstrate that the MPS model successfully schedules more task sets compared to non-preemptive approaches.
Cite as

Benjamin Standaert, Fatima Raadia, Marion Sudvarg, Sanjoy Baruah, Thidapat Chantem, Nathan Fisher, and Christopher Gill. Limited-Preemption EDF Scheduling for Multi-Phase Secure Tasks. In LITES, Volume 10, Issue 1 (2025). Leibniz Transactions on Embedded Systems, Volume 10, Issue 1, pp. 3:1-3:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@Article{standaert_et_al:LITES.10.1.3,
  author =	{Standaert, Benjamin and Raadia, Fatima and Sudvarg, Marion and Baruah, Sanjoy and Chantem, Thidapat and Fisher, Nathan and Gill, Christopher},
  title =	{{Limited-Preemption EDF Scheduling for Multi-Phase Secure Tasks}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{3:1--3:27},
  ISSN =	{2199-2002},
  year =	{2025},
  volume =	{10},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.10.1.3},
  URN =		{urn:nbn:de:0030-drops-230799},
  doi =		{10.4230/LITES.10.1.3},
  annote =	{Keywords: real-time systems, limited-preemption scheduling, trusted execution environments}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2019.20
Fast and Effective Multiframe-Task Parameter Assignment Via Concave Approximations of Demand

Authors: Bo Peng, Nathan Fisher, and Thidapat Chantem

Published in: LIPIcs, Volume 133, 31st Euromicro Conference on Real-Time Systems (ECRTS 2019)

Abstract
Task parameters in traditional models, e.g., the generalized multiframe (GMF) model, are fixed after task specification time. When tasks whose parameters can be assigned within a range, such as the frame parameters in self-suspending tasks and end-to-end tasks, the optimal offline assignment towards schedulability of such parameters becomes important. The GMF-PA (GMF with parameter adaptation) model proposed in recent work allows frame parameters to be flexibly chosen (offline) in arbitrary-deadline systems. Based on the GMF-PA model, a mixed-integer linear programming (MILP)-based schedulability test was previously given under EDF scheduling for a given assignment of frame parameters in uniprocessor systems. Due to the NP-hardness of the MILP, we present a pseudo-polynomial linear programming (LP)-based heuristic algorithm guided by a concave approximation algorithm to achieve a feasible parameter assignment at a fraction of the time overhead of the MILP-based approach. The concave programming approximation algorithm closely approximates the MILP algorithm, and we prove its speed-up factor is (1+delta)^2 where delta > 0 can be arbitrarily small, with respect to the exact schedulability test of GMF-PA tasks under EDF. Extensive experiments involving self-suspending tasks (an application of the GMF-PA model) reveal that the schedulability ratio is significantly improved compared to other previously proposed polynomial-time approaches in medium and moderately highly loaded systems.
Cite as

Bo Peng, Nathan Fisher, and Thidapat Chantem. Fast and Effective Multiframe-Task Parameter Assignment Via Concave Approximations of Demand. In 31st Euromicro Conference on Real-Time Systems (ECRTS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 133, pp. 20:1-20:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

Copy BibTex To Clipboard

@InProceedings{peng_et_al:LIPIcs.ECRTS.2019.20,
  author =	{Peng, Bo and Fisher, Nathan and Chantem, Thidapat},
  title =	{{Fast and Effective Multiframe-Task Parameter Assignment Via Concave Approximations of Demand}},
  booktitle =	{31st Euromicro Conference on Real-Time Systems (ECRTS 2019)},
  pages =	{20:1--20:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-110-8},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{133},
  editor =	{Quinton, Sophie},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2019.20},
  URN =		{urn:nbn:de:0030-drops-107578},
  doi =		{10.4230/LIPIcs.ECRTS.2019.20},
  annote =	{Keywords: generalized multiframe task model (GMF), generalized multiframe task model with parameter adaptation (GMF-PA), self-suspending tasks, uniprocessor scheduling, mixed-integer linear programming, concave approximation, linear programming}
}
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact