An Efficient Fault-Tolerant Scheduling Approach with Energy Minimization for Hard Real-Time Embedded Systems

Kada, Barkahoum; Kalla, Hamoudi

doi:10.2478/cait-2019-0035

Cited by 8 publications

(4 citation statements)

References 31 publications

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“…The performance of the proposed Dyna-QL-Scheduler is compared with existing schedulers by considering with two types of workloads that are BASIC and EXTENDED (EXT). Under EXTENDED workload three distinct types are considered that are EXT_FAIL, EXT_REQ and EXT_ALL [22,23]. For EXT_FAIL workload, higher priority is given for failure of the grid devices and specific requirements of the client tasks are ignored which are managed by EXTENDED workload.…”

Section: Resultsmentioning

confidence: 99%

Uncertainty Aware T2SS Based Dyna-Q-Learning Framework for Task Scheduling in Grid Computing

Bhargavi

Shiva

2022

Cybernetics and Information Technologies

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Task scheduling is an important activity in parallel and distributed computing environment like grid because the performance depends on it. Task scheduling gets affected by behavioral and primary uncertainties. Behavioral uncertainty arises due to variability in the workload characteristics, size of data and dynamic partitioning of applications. Primary uncertainty arises due to variability in data handling capabilities, processor context switching and interplay between the computation intensive applications. In this paper behavioral uncertainty and primary uncertainty with respect to tasks and resources parameters are managed using Type-2-Soft-Set (T2SS) theory. Dyna-Q-Learning task scheduling technique is designed over the uncertainty free tasks and resource parameters. The results obtained are further validated through simulation using GridSim simulator. The performance is good based on metrics such as learning rate, accuracy, execution time and resource utilization rate.

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Section: Resultsmentioning

confidence: 99%

Uncertainty Aware T2SS Based Dyna-Q-Learning Framework for Task Scheduling in Grid Computing

Bhargavi

Shiva

2022

Cybernetics and Information Technologies

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“…Afterward, the greedy algorithm changes the mapping policy and fault-tolerance technique to meet the deadline constraints and reduces energy consumption. The study in [115] has proposed energy-efficient fault-tolerance scheduling for a set of applications with precedence-constrained, which is based on list scheduling heuristics that satisfies the real-time constraints.…”

Section: F Combination Of Several Fault-tolerance Techniquesmentioning

confidence: 99%

A Survey of Fault-Tolerance Techniques for Embedded Systems From the Perspective of Power, Energy, and Thermal Issues

et al. 2022

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The relentless technology scaling has provided a significant increase in processor performance, but on the other hand, it has led to adverse impacts on system reliability. In particular, technology scaling increases the processor susceptibility to radiation-induced transient faults. Moreover, technology scaling with the discontinuation of Dennard scaling increases the power densities, thereby temperatures, on the chip. High temperature, in turn, accelerates transistor aging mechanisms, which may ultimately lead to permanent faults on the chip. To assure a reliable system operation, despite these potential reliability concerns, fault-tolerance techniques have emerged. Specifically, fault-tolerance techniques employ some kind of redundancies to satisfy specific reliability requirements. However, the integration of fault-tolerance techniques into real-time embedded systems complicates preserving timing constraints. As a remedy, many task mapping/scheduling policies have been proposed to consider the integration of fault-tolerance techniques and enforce both timing and reliability guarantees for real-time embedded systems. More advanced techniques aim additionally at minimizing power and energy while at the same time satisfying timing and reliability constraints. Recently, some scheduling techniques have started to tackle a new challenge, which is the temperature increase induced by employing fault-tolerance techniques. These emerging techniques aim at satisfying temperature constraints besides timing and reliability constraints. This paper provides an in-depth survey of the emerging research efforts that exploit fault-tolerance techniques while considering timing, power/energy, and temperature from the real-time embedded systems' design perspective. In particular, the task mapping/scheduling policies for fault-tolerance real-time embedded systems are reviewed and classified according to their considered goals and constraints. Moreover, the employed fault-tolerance techniques, application models, and hardware models are considered as additional dimensions of the presented classification. Lastly, this survey gives deep insights into the main achievements and shortcomings of the existing approaches and highlights the most promising ones.INDEX TERMS Fault-tolerance, embedded systems, real-time computing, scheduling, power/energy minimization, thermal-aware design.

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“…Faults-tolerant algorithms can be either reactive in the sense they handle the faults only when they occur. Whereas, cognitive algorithms can predict and plan in priori the handling of faults (Kandasamy et al, 2000;Mottaghia & Zarandi, 2014;Han, 2015;Fan & al., 2017;Barkahoum & Hamoudi, 2019). Some typical examples of intelligent RT embedded systems scheduling applications include outpatient clinics (OPCs), smart transport and spacecraft.…”

Section: Real Time Schedulingmentioning

confidence: 99%

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

Boutekkouk

2022

International Journal of Cognitive Informatics and Natural Intelligence

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Artificial Intelligence is becoming more attractive to resolve nontrivial problems including the well known real time scheduling (RTS) problem for Embedded Systems (ES). The latter is considered as a hard multi-objective optimization problem because it must optimize at the same time three key conflictual objectives that are tasks deadlines guarantee, energy consumption reduction and reliability enhancement. In this paper, we firstly present the necessary background to well understand the problematic of RTS in the context of ES, then we present our enriched taxonomies for real time, energy and faults tolerance aware scheduling algorithms for ES. After that, we survey the most pertinent existing works of literature targeting the application of AI methods to resolve the RTS problem for ES notably Constraint Programming, Game theory, Machine learning, Fuzzy logic, Artificial Immune Systems, Cellular Automata, Evolutionary algorithms, Multi-agent Systems and Swarm Intelligence. We end this survey by a discussion putting the light on the main challenges and the future directions.

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An Efficient Fault-Tolerant Scheduling Approach with Energy Minimization for Hard Real-Time Embedded Systems

Cited by 8 publications

References 31 publications

Uncertainty Aware T2SS Based Dyna-Q-Learning Framework for Task Scheduling in Grid Computing

Uncertainty Aware T2SS Based Dyna-Q-Learning Framework for Task Scheduling in Grid Computing

A Survey of Fault-Tolerance Techniques for Embedded Systems From the Perspective of Power, Energy, and Thermal Issues

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

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