5 Search Results for "Saifullah, Abusayeed"

Document
DOI: 10.4230/LIPIcs.ECRTS.2024.8
Deadline Miss Early Detection Method for DAG Tasks Considering Variable Execution Time

Authors: Hayate Toba and Takuya Azumi

Published in: LIPIcs, Volume 298, 36th Euromicro Conference on Real-Time Systems (ECRTS 2024)

Abstract
Autonomous driving systems must guarantee safety, which requires strict real-time performance. A series of processes, from sensor data input to vehicle control command output, must be completed by the end-to-end deadline. If a deadline miss occurs, the system must quickly transition to a safe state. To improve safety, an early detection method for deadline misses was proposed. The proposed method represents the autonomous driving system as a directed acyclic graph (DAG) with a mixture of timer-driven and event-driven nodes. It assigns appropriate time constraints for each node based on the end-to-end deadline. However, the existing methods assume the worst-case execution time (WCET) for calculating the time constraints of each node and do not consider the execution time variation of nodes, making the detection of deadline misses pessimistic. This paper proposes a deadline miss early detection method to determine the possibility of deadline misses quantitatively at the beginning of each node execution in a DAG task. It calculates the time constraints of each node using probabilistic execution time, which treats execution time as a random variable. Experimental evaluation shows that the proposed method reduces pessimism, which is a problem of conventional methods using WCET, and then achieves more accurate early detection of deadline misses. The evaluation also indicates that the execution time of static analysis required for deadline miss early detection is within a practical level.
Cite as

Hayate Toba and Takuya Azumi. Deadline Miss Early Detection Method for DAG Tasks Considering Variable Execution Time. In 36th Euromicro Conference on Real-Time Systems (ECRTS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 298, pp. 8:1-8:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{toba_et_al:LIPIcs.ECRTS.2024.8,
  author =	{Toba, Hayate and Azumi, Takuya},
  title =	{{Deadline Miss Early Detection Method for DAG Tasks Considering Variable Execution Time}},
  booktitle =	{36th Euromicro Conference on Real-Time Systems (ECRTS 2024)},
  pages =	{8:1--8:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-324-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{298},
  editor =	{Pellizzoni, Rodolfo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2024.8},
  URN =		{urn:nbn:de:0030-drops-203116},
  doi =		{10.4230/LIPIcs.ECRTS.2024.8},
  annote =	{Keywords: Autonomous driving system, deadline miss early detection, DAG, event-driven task, timer-driven task, probabilistic execution time}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2024.10
Crêpe: Clock-Reconfiguration-Aware Preemption Control in Real-Time Systems with Devices

Authors: Eva Dengler and Peter Wägemann

Published in: LIPIcs, Volume 298, 36th Euromicro Conference on Real-Time Systems (ECRTS 2024)

Abstract
The domain of energy-constrained real-time systems that are operated on modern embedded system-on-chip (SoC) platforms brings numerous novel challenges for optimal resource minimization. These modern hardware platforms offer a heterogeneous variety of features to configure the tradeoff between temporal performance and energy efficiency, which goes beyond the state-of-the-art of existing dynamic-voltage-frequency-scaling (DVFS) scheduling schemes. The control center for configuring this tradeoff on platforms are complex clock subsystems that are intertwined with requirements of the SoC’s components (e.g., transceiver/memory/sensor devices). That is, several devices have precedence constraints with respect to specific clock sources and their settings. The challenge of dynamically adapting the various clock sources to select resource-optimal configurations becomes especially challenging in the presence of asynchronous preemptions, which are inherent to systems that use devices. In this paper, we present Crêpe, an approach to clock-reconfiguration-aware preemption control: Crêpe has an understanding of the target platform’s clock subsystem, its sleep states, and penalties to reconfigure clock sources for adapting clock frequencies. Crêpe’s hardware model is combined with an awareness of the application’s device requirements for each executed task, as well as possible interrupts that cause preemptions during runtime. Using these software/hardware constraints, Crêpe employs, in its offline phase, a mathematical formalization in order to select energy-minimal configurations while meeting given deadlines. This optimizing formalization, processed by standard mathematical solver tools, accounts for potentially occurring interrupts and the respective clock reconfigurations, which are then forwarded as alternative schedules to Crêpe’s runtime system. During runtime, the dispatcher assesses these offline-determined alternative schedules and reconfigures the clock sources for energy minimization. We developed an implementation based on a widely-used SoC platform (i.e., ESP32-C3) and an automated testbed for comprehensive energy-consumption evaluations to validate Crêpe’s claim of selecting resource-optimal settings under worst-case considerations.
Cite as

Eva Dengler and Peter Wägemann. Crêpe: Clock-Reconfiguration-Aware Preemption Control in Real-Time Systems with Devices. In 36th Euromicro Conference on Real-Time Systems (ECRTS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 298, pp. 10:1-10:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{dengler_et_al:LIPIcs.ECRTS.2024.10,
  author =	{Dengler, Eva and W\"{a}gemann, Peter},
  title =	{{Cr\^{e}pe: Clock-Reconfiguration-Aware Preemption Control in Real-Time Systems with Devices}},
  booktitle =	{36th Euromicro Conference on Real-Time Systems (ECRTS 2024)},
  pages =	{10:1--10:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-324-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{298},
  editor =	{Pellizzoni, Rodolfo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2024.10},
  URN =		{urn:nbn:de:0030-drops-203135},
  doi =		{10.4230/LIPIcs.ECRTS.2024.10},
  annote =	{Keywords: energy-constrained real-time systems, time/energy tradeoff, system-on-chip, energy-aware real-time scheduling, resource minimization, preemption control, worst-case energy consumption (WCEC), worst-case execution time (WCET), static whole-system analysis}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2023.8
Precise Scheduling of DAG Tasks with Dynamic Power Management

Authors: Ashikahmed Bhuiyan, Mohammad Pivezhandi, Zhishan Guo, Jing Li, Venkata Prashant Modekurthy, and Abusayeed Saifullah

Published in: LIPIcs, Volume 262, 35th Euromicro Conference on Real-Time Systems (ECRTS 2023)

Abstract
The rigid timing requirement of real-time applications biases the analysis to focus on the worst-case performances. Such a focus cannot provide enough information to optimize the system’s typical resource and energy consumption. In this work, we study the real-time scheduling of parallel tasks on a multi-speed heterogeneous platform while minimizing their typical-case CPU energy consumption. Dynamic power management (DPM) policy is integrated to determine the minimum number of cores required for each task while guaranteeing worst-case execution requirements (under all circumstances). A Hungarian Algorithm-based task partitioning technique is proposed for clustered multi-core platforms, where all cores within the same cluster run at the same speed at any time, while different clusters may run at different speeds. To our knowledge, this is the first work aiming to minimize typical-case CPU energy consumption (while ensuring the worst-case timing correctness for all tasks under any execution condition) through DPM for parallel tasks in a clustered platform. We demonstrate the effectiveness of the proposed approach with existing power management techniques using experimental results and simulations. The experimental results conducted on the Intel Xeon 2680 v3 12-core platform show around 7%-30% additional energy savings.
Cite as

Ashikahmed Bhuiyan, Mohammad Pivezhandi, Zhishan Guo, Jing Li, Venkata Prashant Modekurthy, and Abusayeed Saifullah. Precise Scheduling of DAG Tasks with Dynamic Power Management. In 35th Euromicro Conference on Real-Time Systems (ECRTS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 262, pp. 8:1-8:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{bhuiyan_et_al:LIPIcs.ECRTS.2023.8,
  author =	{Bhuiyan, Ashikahmed and Pivezhandi, Mohammad and Guo, Zhishan and Li, Jing and Modekurthy, Venkata Prashant and Saifullah, Abusayeed},
  title =	{{Precise Scheduling of DAG Tasks with Dynamic Power Management}},
  booktitle =	{35th Euromicro Conference on Real-Time Systems (ECRTS 2023)},
  pages =	{8:1--8:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-280-8},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{262},
  editor =	{Papadopoulos, Alessandro V.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2023.8},
  URN =		{urn:nbn:de:0030-drops-180372},
  doi =		{10.4230/LIPIcs.ECRTS.2023.8},
  annote =	{Keywords: Parallel task, mixed-criticality scheduling, energy minimization, dynamic power management, cluster-based platform}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2020.2
CPU Energy-Aware Parallel Real-Time Scheduling

Authors: Abusayeed Saifullah, Sezana Fahmida, Venkata P. Modekurthy, Nathan Fisher, and Zhishan Guo

Published in: LIPIcs, Volume 165, 32nd Euromicro Conference on Real-Time Systems (ECRTS 2020)

Abstract
Both energy-efficiency and real-time performance are critical requirements in many embedded systems applications such as self-driving car, robotic system, disaster response, and security/safety control. These systems entail a myriad of real-time tasks, where each task itself is a parallel task that can utilize multiple computing units at the same time. Driven by the increasing demand for parallel tasks, multi-core embedded processors are inevitably evolving to many-core. Existing work on real-time parallel tasks mostly focused on real-time scheduling without addressing energy consumption. In this paper, we address hard real-time scheduling of parallel tasks while minimizing their CPU energy consumption on multicore embedded systems. Each task is represented as a directed acyclic graph (DAG) with nodes indicating different threads of execution and edges indicating their dependencies. Our technique is to determine the execution speeds of the nodes of the DAGs to minimize the overall energy consumption while meeting all task deadlines. It incorporates a frequency optimization engine and the dynamic voltage and frequency scaling (DVFS) scheme into the classical real-time scheduling policies (both federated and global) and makes them energy-aware. The contributions of this paper thus include the first energy-aware online federated scheduling and also the first energy-aware global scheduling of DAGs. Evaluation using synthetic workload through simulation shows that our energy-aware real-time scheduling policies can achieve up to 68% energy-saving compared to classical (energy-unaware) policies. We have also performed a proof of concept system evaluation using physical hardware demonstrating the energy efficiency through our proposed approach.
Cite as

Abusayeed Saifullah, Sezana Fahmida, Venkata P. Modekurthy, Nathan Fisher, and Zhishan Guo. CPU Energy-Aware Parallel Real-Time Scheduling. In 32nd Euromicro Conference on Real-Time Systems (ECRTS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 165, pp. 2:1-2:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{saifullah_et_al:LIPIcs.ECRTS.2020.2,
  author =	{Saifullah, Abusayeed and Fahmida, Sezana and Modekurthy, Venkata P. and Fisher, Nathan and Guo, Zhishan},
  title =	{{CPU Energy-Aware Parallel Real-Time Scheduling}},
  booktitle =	{32nd Euromicro Conference on Real-Time Systems (ECRTS 2020)},
  pages =	{2:1--2:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-152-8},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{165},
  editor =	{V\"{o}lp, Marcus},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2020.2},
  URN =		{urn:nbn:de:0030-drops-123655},
  doi =		{10.4230/LIPIcs.ECRTS.2020.2},
  annote =	{Keywords: Real-time scheduling, multicore, energy-efficiency, embedded systems}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2017.22
Energy-Efficient Multi-Core Scheduling for Real-Time DAG Tasks

Authors: Zhishan Guo, Ashikahmed Bhuiyan, Abusayeed Saifullah, Nan Guan, and Haoyi Xiong

Published in: LIPIcs, Volume 76, 29th Euromicro Conference on Real-Time Systems (ECRTS 2017)

Abstract
In this work, we study energy-aware real-time scheduling of a set of sporadic Directed Acyclic Graph (DAG) tasks with implicit deadlines. While meeting all real-time constraints, we try to identify the best task allocation and execution pattern such that the average power consumption of the whole platform is minimized. To the best of our knowledge, this is the first work that addresses the power consumption issue in scheduling multiple DAG tasks on multi-cores and allows intra-task processor sharing. We first adapt the decomposition-based framework for federated scheduling and propose an energy-sub-optimal scheduler. Then we derive an approximation algorithm to identify processors to be merged together for further improvements in energy-efficiency and to prove the bound of the approximation ratio. We perform a simulation study to demonstrate the effectiveness and efficiency of the proposed scheduling. The simulation results show that our algorithms achieve an energy saving of 27% to 41% compared to existing DAG task schedulers.
Cite as

Zhishan Guo, Ashikahmed Bhuiyan, Abusayeed Saifullah, Nan Guan, and Haoyi Xiong. Energy-Efficient Multi-Core Scheduling for Real-Time DAG Tasks. In 29th Euromicro Conference on Real-Time Systems (ECRTS 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 76, pp. 22:1-22:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{guo_et_al:LIPIcs.ECRTS.2017.22,
  author =	{Guo, Zhishan and Bhuiyan, Ashikahmed and Saifullah, Abusayeed and Guan, Nan and Xiong, Haoyi},
  title =	{{Energy-Efficient Multi-Core Scheduling for Real-Time DAG Tasks}},
  booktitle =	{29th Euromicro Conference on Real-Time Systems (ECRTS 2017)},
  pages =	{22:1--22:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-037-8},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{76},
  editor =	{Bertogna, Marko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2017.22},
  URN =		{urn:nbn:de:0030-drops-71675},
  doi =		{10.4230/LIPIcs.ECRTS.2017.22},
  annote =	{Keywords: Parallel task, Real-time scheduling, Energy minimization, Convex optimization}
}
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