Research on Task Scheduling Strategy based on the Trustworthiness of MapReduce

Qin Jun, Song Yanyan, Zong Ping
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Abstract

With the rapid development and popularization of information technology, cloud computing technology provides a good environment for solving massive data processing. Hadoop is an open-source implementation of MapReduce and has the ability to process large amounts of data. Aiming at the shortcomings of the fault-tolerant technology in the MapReduce programming model, this paper proposes a reliability task scheduling strategy that introduces a failure recovery mechanism, evaluates the trustworthiness of resource nodes in the cloud environment, establishes a trustworthiness model, and avoids task allocation to low reliability node, causing the task to be re-executed, wasting time and resources. Finally, the simulation platform CloudSim verifies the validity and stability of the task scheduling algorithm and scheduling model proposed in this paper.
基于MapReduce可信度的任务调度策略研究
随着信息技术的快速发展和普及,云计算技术为解决海量数据处理提供了良好的环境。Hadoop是MapReduce的开源实现,具有处理大量数据的能力。针对MapReduce编程模型中容错技术的不足,本文提出了一种可靠性任务调度策略,引入故障恢复机制,对云环境中资源节点的可信度进行评估,建立可信度模型,避免将任务分配给低可靠性节点,导致任务重新执行,浪费时间和资源。最后,仿真平台CloudSim验证了本文提出的任务调度算法和调度模型的有效性和稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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