Reliability Aware Energy Optimized Scheduling of Non-Preemptive Periodic Real-Time Tasks on Heterogeneous Multiprocessor System

Kumar, Niraj; Mayank, Jaishree; Mondal, Arijit

doi:10.1109/tpds.2019.2950251

Cited by 34 publications

(6 citation statements)

References 33 publications

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“…Task replication techniques are widely used in fault-tolerant scheduling algorithms for multi-core systems. However, redundant task replicas cause a surge in energy consumption while guaranteeing the reliability of task execution [2]. Therefore, how to save energy in scheduling algorithms based on task replication techniques has become a concern for scholars.…”

Section: Motivationmentioning

confidence: 99%

“…Niraj Kumar et al in [2] discussed the reliable energy-efficient scheduling of nonpreemptive real-time tasks in heterogeneous multi-core processing systems, but the diverse ideas presented in their discussion about heterogeneous multi-core systems is reflected in the fact that each core can independently adjust its operating frequency without discussing the heterogeneity of the hardware parameters of the processor cores.…”

Section: Related Workmentioning

confidence: 99%

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Energy-Saving Task Scheduling Based on Hard Reliability Requirements: A Novel Approach with Low Energy Consumption and High Reliability

Chen

Han

et al. 2022

Sustainability

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With the increasing complexity of application situations in multi-core processing systems, how to assure task execution reliability has become a focus of scheduling algorithm research in recent years. Most fault-tolerant algorithms achieve hard reliability requirements through task redundancy, which increases energy consumption and contradicts the concept of sustainable development. In this paper, we propose a new algorithm called HDFE (Heterogeneous-Dag-task-fault-tolerance-energy-efficiency algorithm) that combines DVFS technology and task replication technology to solve the scheduling problem of DAG applications concerning energy-saving and hard reliability requirements in heterogeneous multi-core processor systems. Our algorithm is divided into three phases: the priority calculation phase, the task replication phase, and the task assignment phase. The HDFE algorithm achieved energy savings while meeting hard reliability requirements for applications, which was based on the interrelationship between reliability and energy consumption in filtering task replicas. In the experimental part of this paper, we designed four comparison experiments between the EFSRG algorithm, the HRRM algorithm, and the HDFE algorithm. The experimental results showed that the energy consumption of task scheduling using the HDFE algorithm is lower than other algorithms under different scales, thus achieving energy savings and complying with the concept of sustainable development.

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Section: Motivationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Energy-Saving Task Scheduling Based on Hard Reliability Requirements: A Novel Approach with Low Energy Consumption and High Reliability

Chen

Han

et al. 2022

Sustainability

View full text Add to dashboard Cite

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“…An improved bi‐objective genetic algorithm to optimize the energy consumption and reliability of the task scheduling problem in multiprocessing systems was proposed by Zhang et al, 20 which assumes that there is no memory contention on the same processor core, but this is often not the case in reality. A strategy based on active replication was proposed by Kumar et al 21 to improve the reliability of the system, in addition to a scheduling strategy that integrates the processor frequency and the number of replicas to further reduce the energy consumption. But it only considers the periodic tasks and does not consider the inter‐dependencies between tasks.…”

Section: Related Workmentioning

confidence: 99%

Time‐constrained and reliability aware energy minimization scheduling algorithm for heterogeneous multiprocessor environments

Wang

Fan

2022

Concurrency and Computation

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Heterogeneous multiprocessor systems are now widely used in industry by providing high performance and high concurrency. However, with the increasing number of computational nodes, it leads to a dramatic increase in energy consumption of heterogeneous multiprocessor systems. Most of the current research has been conducted to reduce the energy consumption by reducing the processor frequency and extending the task execution time, but these measures often lead to a significant decrease in system reliability. This article addresses the problem of energy-aware task scheduling in the case of distributed computing systems with deadline and reliability constraints.First, a time and reliability allocation model is built to assign the deadline and reliability constraints to each task, which ensures fairness among tasks. Then, a three-stage scheduling algorithm is proposed to minimize the system energy consumption. The static energy consumption is minimized by shutting down the inefficient processors.The dynamic energy consumption of the system is reduced by distributing tasks as evenly as possible on each processor through a task redistribution strategy. Finally, experimental results on real scientific workflows and randomly generated graphs show that the proposed algorithm outperforms other algorithms in terms of energy reduction.

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“…This paper Distributed Processing System studies hard RT systems. Compared with general-purpose computers, RT systems have several important characteristics [7][8]:…”

Section: Heterogeneous Rt Systemsmentioning

confidence: 99%

Fault-tolerant Scheduling Algorithm for Real-time Periodic Tasks in Heterogeneous Distributed Systems Based on Discrete Logarithmic Multi-signature

2022

DPS

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Heterogeneous processors have high performance and low energy consumption, so they are widely used in various real-time(RT) systems, such as flight control systems. In a RT system, tasks that fail to meet deadlines can have catastrophic consequences. In order to avoid the situation that the system failure causes the task to miss the deadline, it is necessary to provide the system with fault tolerance. Fault-tolerant scheduling is an effective way to achieve system fault tolerance. There are two types of system faults: transient faults and permanent faults. The purpose of this paper is to study the fault-tolerant scheduling algorithm of RT periodic tasks in heterogeneous distributed systems based on discrete logarithmic multi-signature. This paper studies the transient fault tolerance problem. Existing transient fault-tolerant algorithms only consider fault-tolerance and ignore the RT nature of tasks. Therefore, considering both fault tolerance and time constraints, this paper proposes a transient fault-tolerant scheduling algorithm DB-FTSA based on time deadlines. According to the time deadline, calculate the number of fault-tolerant tasks that can provide fault tolerance, and give priority to fault tolerance of high-priority tasks. Configuration improves system reliability. At the same time, the algorithm fully considers the setup time and task execution time, making the algorithm closer to reality and more accurate. In order to overcome the problem that the traditional dynamic programming algorithm does not support a single type of sub-module, the algorithm uses active and passive sub-modules to achieve fault tolerance to reduce sub-module redundancy. It has been experimentally proven that, therefore, large tasks should be replaced with as many small tasks as possible to reduce the number of processors required.

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Reliability Aware Energy Optimized Scheduling of Non-Preemptive Periodic Real-Time Tasks on Heterogeneous Multiprocessor System

Cited by 34 publications

References 33 publications

Energy-Saving Task Scheduling Based on Hard Reliability Requirements: A Novel Approach with Low Energy Consumption and High Reliability

Energy-Saving Task Scheduling Based on Hard Reliability Requirements: A Novel Approach with Low Energy Consumption and High Reliability

Time‐constrained and reliability aware energy minimization scheduling algorithm for heterogeneous multiprocessor environments

Fault-tolerant Scheduling Algorithm for Real-time Periodic Tasks in Heterogeneous Distributed Systems Based on Discrete Logarithmic Multi-signature

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