Dynamic Fault-Tolerant Workflow Scheduling with Hybrid Spatial-Temporal Re-Execution in Clouds

Wu, Na; Zuo, Decheng; Zhang, Zhan

doi:10.3390/info10050169

Cited by 15 publications

(10 citation statements)

References 37 publications

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“…With the development and universal application of microcomputers, fault-tolerant technology has developed rapidly in multiprocessor systems, flying hoc networks, cloud computing, wireless sensor networks and so on [1][2][3][4]. In recent years, fault-tolerant technology has also received extensive attention in the field of multi-phase motor control.…”

Section: Introductionmentioning

confidence: 99%

Fault-Tolerant Control Strategy for 12-Phase Permanent Magnet Synchronous Motor

et al. 2019

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Multi-phase motors have attracted increasing attention in fields seeking high reliability, such as electric vehicles, ships, and rail transit, as they exhibit advantages, such as high reliability and fault tolerance. In this study, we consider a 12-phase permanent magnet synchronous motor (PMSM). First, a mathematical model of the 12-phase PMSM in the static coordinate system is established and the model is simplified according to the constraint condition of neutral point isolation. Second, according to the principle of invariant magnetomotive force under normal and fault conditions, two optimal control strategies of winding current, i.e. maximum torque output (MTO) and minimum copper consumption (MCC), are proposed. For a single-phase open-circuit fault, two optimization methods are used to reconstruct the residual phase current, such that the motor can maintain normal torque output and exhibit lower torque ripple under the fault state. Finally, system simulation and experimental research are conducted; the results verify the accuracy and feasibility of the fault-tolerant control strategy of the 12-phase PMSM proposed in this paper.

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Section: Introductionmentioning

confidence: 99%

Fault-Tolerant Control Strategy for 12-Phase Permanent Magnet Synchronous Motor

et al. 2019

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“…The proposed CEHFTS model is compared with the Spatial-Temporal Re-Execution method (SRE) [10]. The NASA workload [14] has been used as the emulator of Web users requests to the Access Point (AP).…”

Section: Resultsmentioning

confidence: 99%

“…For important jobs or tasks with permanent failures, the dynamic fault-tolerant workflow scheduling [10] uses spatial re-execution (SRE) and temporal re-execution (TRE) schemes in unison. However, as the number of issues detected for important operations is greater, the SRE strategy consumes more disc space.…”

Section: Motivation and Objectivesmentioning

confidence: 99%

Cost Effective Hybrid Fault Tolerant Scheduling Model for Cloud Computing Environment

Sheetal¹,

Ravindranath²

2021

IJACSA

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Cloud computing provides flexible and cost effective way for end users to access data from multiplatform environment. Despite of support by the features of cloud computing, there are also chances of resource failure. Hence there is a need of a fault tolerant mechanism to achieve undisrupted performance of cloud services. The task reallocation and duplication are the two commonly used fault tolerant mechanisms. But task replication method results in huge storage and computational overhead, when the number of tasks is increasing gradually. If the number of faults is high, it incurs more storage overhead and time complexity based on task criticality. In order to solve these issues, we propose to develop a Cost Effective Hybrid Fault Tolerant Scheduling (CEHFTS) Model for cloud computing. In this model, the Failure Occurrence Probability (FoP) of each VM is estimated by finding the previous failures and successful executions. Then an adaptive fault recovery timer is maintained during a fault, which is adjusted based on the type of faults. Experimental results have shown that CEHFTS model achieves 43% reduced storage cost and 13% reduced response delay for critical tasks, when compared to existing technique.

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“…The proposed model uses Pareto front solutions to achieve at least as good as scheduling results instead of repeatedly implementing the single-objective scheduling algorithm with multiple constraints. Furthermore, the authors [44] proposed a dynamic fault-tolerant workflow scheduling (DFTWS) approach with hybrid spatial and temporary re-implementation schemes. Firstly, DFTWS calculates the time characteristics of each task and predicts the critical path of the workflows.…”

Section: Workflow Schedulingmentioning

confidence: 99%

Multi-Dependency and Time Based Resource Scheduling Algorithm for Scientific Applications in Cloud Computing

2021

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Workflow scheduling is one of the significant issues for scientific applications among virtual machine migration, database management, security, performance, fault tolerance, server consolidation, etc. In this paper, existing time-based scheduling algorithms, such as first come first serve (FCFS), min–min, max–min, and minimum completion time (MCT), along with dependency-based scheduling algorithm MaxChild have been considered. These time-based scheduling algorithms only compare the burst time of tasks. Based on the burst time, these schedulers, schedule the sub-tasks of the application on suitable virtual machines according to the scheduling criteria. During this process, not much attention was given to the proper utilization of the resources. A novel dependency and time-based scheduling algorithm is proposed that considers the parent to child (P2C) node dependencies, child to parent node dependencies, and the time of different tasks in the workflows. The proposed P2C algorithm emphasizes proper utilization of the resources and overcomes the limitations of these time-based schedulers. The scientific applications, such as CyberShake, Montage, Epigenomics, Inspiral, and SIPHT, are represented in terms of the workflow. The tasks can be represented as the nodes, and relationships between the tasks can be represented as the dependencies in the workflows. All the results have been validated by using the simulation-based environment created with the help of the WorkflowSim simulator for the cloud environment. It has been observed that the proposed approach outperforms the mentioned time and dependency-based scheduling algorithms in terms of the total execution time by efficiently utilizing the resources.

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Dynamic Fault-Tolerant Workflow Scheduling with Hybrid Spatial-Temporal Re-Execution in Clouds

Cited by 15 publications

References 37 publications

Fault-Tolerant Control Strategy for 12-Phase Permanent Magnet Synchronous Motor

Fault-Tolerant Control Strategy for 12-Phase Permanent Magnet Synchronous Motor

Cost Effective Hybrid Fault Tolerant Scheduling Model for Cloud Computing Environment

Multi-Dependency and Time Based Resource Scheduling Algorithm for Scientific Applications in Cloud Computing

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