11 Search Results for "Guo, Zhishan"

Document
DOI: 10.4230/LITES.11.1.1
A Survey of Real-Time Support, Analysis, and Advancements in ROS 2

Authors: Daniel Casini, Jian-Jia Chen, Jing Li, Federico Reghenzani, and Harun Teper

Published in: LITES, Volume 11, Issue 1 (2026). Leibniz Transactions on Embedded Systems, Volume 11, Issue 1

Abstract
The Robot Operating System 2 (ROS 2) has emerged as a relevant middleware framework for robotic applications, offering modularity, distributed execution, and communication. In the last six years, ROS 2 has drawn increasing attention from the real-time systems community and industry. This survey presents a comprehensive overview of research efforts that analyze, enhance, and extend ROS 2 to support real-time execution. We first provide a detailed description of the internal scheduling mechanisms of ROS 2 and its layered architecture, including the interaction with DDS-based communication and other communication middleware. We then review key contributions from the literature, covering timing analysis for both single- and multi-threaded executors, metrics such as response time, reaction time, and data age, and different communication modes. The survey also discusses community-driven enhancements to the ROS 2 runtime, including new executor algorithm designs, real-time GPU management, and microcontroller support via micro-ROS. Furthermore, we summarize techniques for bounding DDS communication delays, message filters, and profiling tools that have been developed to support analysis and experimentation. To help systematize this growing body of work, we introduce taxonomies that classify the surveyed contributions based on different criteria. This survey aims to guide both researchers and practitioners in understanding and improving the real-time capabilities of ROS 2.
Cite as

Daniel Casini, Jian-Jia Chen, Jing Li, Federico Reghenzani, and Harun Teper. A Survey of Real-Time Support, Analysis, and Advancements in ROS 2. In LITES, Volume 11, Issue 1 (2026). Leibniz Transactions on Embedded Systems, Volume 11, Issue 1, pp. 1:1-1:37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{casini_et_al:LITES.11.1.1,
  author =	{Casini, Daniel and Chen, Jian-Jia and Li, Jing and Reghenzani, Federico and Teper, Harun},
  title =	{{A Survey of Real-Time Support, Analysis, and Advancements in ROS 2}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{1:1--1:37},
  ISSN =	{2199-2002},
  year =	{2026},
  volume =	{11},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.11.1.1},
  URN =		{urn:nbn:de:0030-drops-257914},
  doi =		{10.4230/LITES.11.1.1},
  annote =	{Keywords: ROS 2, middleware, real-time, timing predictability, publish-subscribe}
}
Document
DOI: 10.4230/LITES.10.2.2
Improved Elastic Scheduling Algorithms for Implicit-Deadline Tasks

Authors: Marion Sudvarg, Christopher Gill, and Sanjoy Baruah

Published in: LITES, Volume 10, Issue 2 (2025): Special Issue on Industrial Real-Time Systems. Leibniz Transactions on Embedded Systems, Volume 10, Issue 2

Abstract
Elastic scheduling provides a framework under which the utilizations of recurrent tasks are reduced by increasing their periods in response to system overload. The original elastic scheduling model was proposed by Buttazzo et al. in 1998 for implicit-deadline tasks on a uniprocessor and decreases task utilizations to satisfy a schedulable utilization bound. In 2019, Orr and Baruah extended the framework to multiprocessor scheduling of implicit-deadline tasks. In this paper, we propose, analyze, and evaluate new elastic scheduling algorithms for several of the scheduling policies considered in these prior works. In particular, (i) we evaluate an algorithm that we proposed as a short note in the Real-Time Systems journal and demonstrate that it allows for faster admission control than the algorithm of Buttazzo et al. when applied to uniprocessor and fluid scheduling. (ii) We also present faster elastic scheduling algorithms for partitioned EDF scheduling. Finally, (iii) we provide polynomial-time exact elastic scheduling algorithms for global EDF and global RM.
Cite as

Marion Sudvarg, Christopher Gill, and Sanjoy Baruah. Improved Elastic Scheduling Algorithms for Implicit-Deadline Tasks. In LITES, Volume 10, Issue 2 (2025): Special Issue on Industrial Real-Time Systems. Leibniz Transactions on Embedded Systems, Volume 10, Issue 2, pp. 2:1-2:36, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{sudvarg_et_al:LITES.10.2.2,
  author =	{Sudvarg, Marion and Gill, Christopher and Baruah, Sanjoy},
  title =	{{Improved Elastic Scheduling Algorithms for Implicit-Deadline Tasks}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{2:1--2:36},
  ISSN =	{2199-2002},
  year =	{2025},
  volume =	{10},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES.10.2.2},
  URN =		{urn:nbn:de:0030-drops-252346},
  doi =		{10.4230/LITES.10.2.2},
  annote =	{Keywords: real-time systems, elastic scheduling, scheduling algorithms}
}
Document
Artifact
DOI: 10.4230/DARTS.11.1.4
Faster Classification of Time-Series Input Streams (Artifact)

Authors: Kunal Agrawal, Sanjoy Baruah, Zhishan Guo, Jing Li, Federico Reghenzani, Kecheng Yang, and Jinhao Zhao

Published in: DARTS, Volume 11, Issue 1, Special Issue of the 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)

Abstract
Deep learning–based classifiers are widely used for perception in autonomous Cyber-Physical Systems (CPS’s). However, such classifiers rarely offer guarantees of perfect accuracy while being optimized for efficiency. To support safety-critical perception, ensembles of multiple different classifiers working in concert are typically used. Since CPS’s interact with the physical world continuously, it is not unreasonable to expect dependencies among successive inputs in a stream of sensor data. Prior work introduced a classification technique that leverages these inter-input dependencies to reduce the average time to successful classification using classifier ensembles. In this paper, we propose generalizations to this classification technique, both in the improved generation of classifier cascades and the modeling of temporal dependencies. We demonstrate, through theoretical analysis and numerical evaluation, that our approach achieves further reductions in average classification latency compared to the prior methods.
Cite as

Kunal Agrawal, Sanjoy Baruah, Zhishan Guo, Jing Li, Federico Reghenzani, Kecheng Yang, and Jinhao Zhao. Faster Classification of Time-Series Input Streams (Artifact). In Special Issue of the 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Dagstuhl Artifacts Series (DARTS), Volume 11, Issue 1, pp. 4:1-4:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{agrawal_et_al:DARTS.11.1.4,
  author =	{Agrawal, Kunal and Baruah, Sanjoy and Guo, Zhishan and Li, Jing and Reghenzani, Federico and Yang, Kecheng and Zhao, Jinhao},
  title =	{{Faster Classification of Time-Series Input Streams (Artifact)}},
  pages =	{4:1--4:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2025},
  volume =	{11},
  number =	{1},
  editor =	{Agrawal, Kunal and Baruah, Sanjoy and Guo, Zhishan and Li, Jing and Reghenzani, Federico and Yang, Kecheng and Zhao, Jinhao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.11.1.4},
  URN =		{urn:nbn:de:0030-drops-236057},
  doi =		{10.4230/DARTS.11.1.4},
  annote =	{Keywords: Classification, Deep Learning, Sensor data streams, IDK classifiers}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2025.12
Real-Time System Evaluation Techniques: A Systematic Mapping Study

Authors: Tilmann L. Unte and Sebastian Altmeyer

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

Abstract
A systematic mapping study assesses a broad selection of research publications with the aim of categorizing them according to a research question. We present the first systematic mapping study on evaluation practices within the field of real-time systems, by analyzing publications from the top three conferences ECRTS, RTAS, and RTSS from 2017 until 2024. Our study provides a comprehensive view on the evaluation practices prevalent in our community, including benchmark software, task set and graph generators, case studies, industrial challenges, and custom solutions. Based on our study, we construct and publish a dataset enabling quantitative analysis of evaluation practices within the real-time systems community. Our analysis indicates shortcomings in current practice: custom case studies are abundant, while industrial challenges have very minor impact. Reproducibility has only been shown for a small subset of evaluations and there is no indication of change. Adoption of new and improved tools and benchmarks is very slow or even non-existent. Evaluation must not be viewed as an obligation when publishing a paper, but as a key element in ensuring practicability, comparability, and reproducibility. Based on our study, we conclude that our community currently falls short on these objectives.
Cite as

Tilmann L. Unte and Sebastian Altmeyer. Real-Time System Evaluation Techniques: A Systematic Mapping Study. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 12:1-12:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{unte_et_al:LIPIcs.ECRTS.2025.12,
  author =	{Unte, Tilmann L. and Altmeyer, Sebastian},
  title =	{{Real-Time System Evaluation Techniques: A Systematic Mapping Study}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{12:1--12:21},
  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.2025.12},
  URN =		{urn:nbn:de:0030-drops-235903},
  doi =		{10.4230/LIPIcs.ECRTS.2025.12},
  annote =	{Keywords: Systematic Mapping Study, Real-Time Systems, Evaluation}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2025.13
Faster Classification of Time-Series Input Streams

Authors: Kunal Agrawal, Sanjoy Baruah, Zhishan Guo, Jing Li, Federico Reghenzani, Kecheng Yang, and Jinhao Zhao

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

Abstract
Deep learning–based classifiers are widely used for perception in autonomous Cyber-Physical Systems (CPS’s). However, such classifiers rarely offer guarantees of perfect accuracy while being optimized for efficiency. To support safety-critical perception, ensembles of multiple different classifiers working in concert are typically used. Since CPS’s interact with the physical world continuously, it is not unreasonable to expect dependencies among successive inputs in a stream of sensor data. Prior work introduced a classification technique that leverages these inter-input dependencies to reduce the average time to successful classification using classifier ensembles. In this paper, we propose generalizations to this classification technique, both in the improved generation of classifier cascades and the modeling of temporal dependencies. We demonstrate, through theoretical analysis and numerical evaluation, that our approach achieves further reductions in average classification latency compared to the prior methods.
Cite as

Kunal Agrawal, Sanjoy Baruah, Zhishan Guo, Jing Li, Federico Reghenzani, Kecheng Yang, and Jinhao Zhao. Faster Classification of Time-Series Input Streams. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 13:1-13:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{agrawal_et_al:LIPIcs.ECRTS.2025.13,
  author =	{Agrawal, Kunal and Baruah, Sanjoy and Guo, Zhishan and Li, Jing and Reghenzani, Federico and Yang, Kecheng and Zhao, Jinhao},
  title =	{{Faster Classification of Time-Series Input Streams}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{13:1--13:22},
  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.2025.13},
  URN =		{urn:nbn:de:0030-drops-235919},
  doi =		{10.4230/LIPIcs.ECRTS.2025.13},
  annote =	{Keywords: Classification, Deep Learning, Sensor data streams, IDK classifiers}
}
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/LITES-v005-i001-a001
Risk-Aware Scheduling of Dual Criticality Job Systems Using Demand Distributions

Authors: Bader Naim Alahmad and Sathish Gopalakrishnan

Published in: LITES, Volume 5, Issue 1 (2018). Leibniz Transactions on Embedded Systems, Volume 5, Issue 1

Abstract
We pose the problem of scheduling Mixed Criticality (MC) job systems when there are only two criticality levels, Lo and Hi -referred to as Dual Criticality job systems- on a single processing platform, when job demands are probabilistic and their distributions are known. The current MC models require that the scheduling policy allocate as little execution time as possible to Lo-criticality jobs if the scenario of execution is of Hi criticality, and drop Lo-criticality jobs entirely as soon as the execution scenario's criticality level can be inferred and is Hi. The work incurred by "incorrectly" scheduling Lo-criticality jobs in cases of Hi realized scenarios might affect the feasibility of Hi criticality jobs; we quantify this work and call it Work Threatening Feasibility (WTF). Our objective is to construct online scheduling policies that minimize the expected WTF for the given instance, and under which the instance is feasible in a probabilistic sense that is consistent with the traditional deterministic definition of MC feasibility. We develop a probabilistic framework for MC scheduling, where feasibility is defined in terms of (chance) constraints on the probabilities that Lo and Hi jobs meet their deadlines. The probabilities are computed over the set of sample paths, or trajectories, induced by executing the policy, and those paths are dependent upon the set of execution scenarios and the given demand distributions. Our goal is to exploit the information provided by job distributions to compute the minimum expected WTF below which the given instance is not feasible in probability, and to compute a (randomized) "efficiently implementable" scheduling policy that realizes the latter quantity. We model the problem as a Constrained Markov Decision Process (CMDP) over a suitable state space and a finite planning horizon, and show that an optimal (non-stationary) Markov randomized scheduling policy exists. We derive an optimal policy by solving a Linear Program (LP). We also carry out quantitative evaluations on select probabilistic MC instances to demonstrate that our approach potentially outperforms current MC scheduling policies.
Cite as

Bader Naim Alahmad and Sathish Gopalakrishnan. Risk-Aware Scheduling of Dual Criticality Job Systems Using Demand Distributions. In LITES, Volume 5, Issue 1 (2018). Leibniz Transactions on Embedded Systems, Volume 5, Issue 1, pp. 01:1-01:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@Article{alahmad_et_al:LITES-v005-i001-a001,
  author =	{Alahmad, Bader Naim and Gopalakrishnan, Sathish},
  title =	{{Risk-Aware Scheduling of Dual Criticality Job Systems Using Demand Distributions}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{01:1--01:30},
  ISSN =	{2199-2002},
  year =	{2018},
  volume =	{5},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES-v005-i001-a001},
  URN =		{urn:nbn:de:0030-drops-192720},
  doi =		{10.4230/LITES-v005-i001-a001},
  annote =	{Keywords: Mixed criticalities, Probability distribution, Real time systems, Scheduling, Chance constrained Markov decision process, Linear programming, Randomized policy}
}
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}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2016.7
Mixed-Criticality Scheduling to Minimize Makespan

Authors: Sanjoy Baruah, Arvind Easwaran, and Zhishan Guo

Published in: LIPIcs, Volume 65, 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016)

Abstract
In the mixed-criticality job model, each job is characterized by two execution time parameters, representing a smaller (less conservative) estimate and a larger (more conservative) estimate on its actual, unknown, execution time. Each job is further classified as being either less critical or more critical. The desired execution semantics are that all jobs should execute correctly provided all jobs complete upon being allowed to execute for up to the smaller of their execution time estimates, whereas if some jobs need to execute beyond their smaller execution time estimates (but not beyond their larger execution time estimates), then only the jobs classified as being more critical are required to execute correctly. The scheduling of collections of such mixed-criticality jobs upon identical multiprocessor platforms in order to minimize the makespan is considered here.
Cite as

Sanjoy Baruah, Arvind Easwaran, and Zhishan Guo. Mixed-Criticality Scheduling to Minimize Makespan. In 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 65, pp. 7:1-7:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{baruah_et_al:LIPIcs.FSTTCS.2016.7,
  author =	{Baruah, Sanjoy and Easwaran, Arvind and Guo, Zhishan},
  title =	{{Mixed-Criticality Scheduling to Minimize Makespan}},
  booktitle =	{36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016)},
  pages =	{7:1--7:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-027-9},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{65},
  editor =	{Lal, Akash and Akshay, S. and Saurabh, Saket and Sen, Sandeep},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2016.7},
  URN =		{urn:nbn:de:0030-drops-68429},
  doi =		{10.4230/LIPIcs.FSTTCS.2016.7},
  annote =	{Keywords: Scheduling, Mixed criticality, Identical parallel machines, Makespan minimization, Approximation algorithm.}
}
Document
DOI: 10.4230/LITES-v001-i002-a003
Implementing Mixed-criticality Systems Upon a Preemptive Varying-speed Processor

Authors: Zhishan Guo and Sanjoy K. Baruah

Published in: LITES, Volume 1, Issue 2 (2014). Leibniz Transactions on Embedded Systems, Volume 1, Issue 2

Abstract
A mixed criticality (MC) workload consists of components of varying degrees of importance (or "criticalities"); the more critical components typically need to have their correctness validated to greater levels of assurance than the less critical ones. The problem of executing such a MC workload upon a preemptive processor whose effective speed may vary during run-time, in a manner that is not completely known prior to run-time, is considered.Such a processor is modeled as being characterized by several execution speeds: a normal speed and several levels of degraded speed. Under normal circumstances it will execute at or above its normal speed; conditions during run-time may cause it to execute slower. It is desired that all components of the MC workload execute correctly under normal circumstances. If the processor speed degrades, it should nevertheless remain the case that the more critical components execute correctly (although the less critical ones need not do so).In this work, we derive an optimal algorithm for scheduling MC workloads upon such platforms; achieving optimality does not require that the processor be able to monitor its own run-time speed. For the sub-case of the general problem where there are only two criticality levels defined, we additionally provide an implementation that is asymptotically optimal in terms of run-time efficiency.
Cite as

Zhishan Guo and Sanjoy K. Baruah. Implementing Mixed-criticality Systems Upon a Preemptive Varying-speed Processor. In LITES, Volume 1, Issue 2 (2014). Leibniz Transactions on Embedded Systems, Volume 1, Issue 2, pp. 03:1-03:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

Copy BibTex To Clipboard

@Article{guo_et_al:LITES-v001-i002-a003,
  author =	{Guo, Zhishan and Baruah, Sanjoy K.},
  title =	{{Implementing Mixed-criticality Systems Upon a Preemptive Varying-speed Processor}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{03:1--03:19},
  ISSN =	{2199-2002},
  year =	{2014},
  volume =	{1},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES-v001-i002-a003},
  URN =		{urn:nbn:de:0030-drops-192498},
  doi =		{10.4230/LITES-v001-i002-a003},
  annote =	{Keywords: Mixed criticalities, Varying-speed processor, Preemptive uniprocessor scheduling, }
}
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