基于可信度的任务调度策略研究

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS International Journal of Parallel Emergent and Distributed Systems Pub Date : 2021-09-30 DOI:10.5121/ijdps.2021.12501
Jun Qin, Yanyan Song, Ping Zong
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引用次数: 0

摘要

MapReduce是一种用于云计算处理海量数据的分布式计算模型。它简化了分布式并行程序的编写。对于MapReduce编程模型中的容错技术,可能会将任务分配给可靠性较低的节点。这会导致任务被重新执行,浪费时间和资源。提出了一种带故障恢复机制的可靠性任务调度策略,评估了云环境下资源节点的可信度,建立了可信度模型。利用仿真平台CloudSim,验证了任务调度算法和调度模型的稳定性。
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Study of Task Scheduling Strategy based on Trustworthiness
MapReduce is a distributed computing model for cloud computing to process massive data. It simplifies the writing of distributed parallel programs. For the fault-tolerant technology in the MapReduce programming model, tasks may be allocated to nodes with low reliability. It causes the task to be reexecuted, wasting time and resources. This paper proposes a reliability task scheduling strategy with a failure recovery mechanism, evaluates the trustworthiness of resource nodes in the cloud environment and builds a trustworthiness model. By using the simulation platform CloudSim, the stability of the task scheduling algorithm and scheduling model are verified in this paper.
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CiteScore
2.30
自引率
0.00%
发文量
27
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