基于MapReduce可信度的任务调度策略研究

Qin Jun, Song Yanyan, Zong Ping
{"title":"基于MapReduce可信度的任务调度策略研究","authors":"Qin Jun, Song Yanyan, Zong Ping","doi":"10.5121/csit.2021.111304","DOIUrl":null,"url":null,"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.","PeriodicalId":104179,"journal":{"name":"AI, Machine Learning and Applications","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Task Scheduling Strategy based on the Trustworthiness of MapReduce\",\"authors\":\"Qin Jun, Song Yanyan, Zong Ping\",\"doi\":\"10.5121/csit.2021.111304\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":104179,\"journal\":{\"name\":\"AI, Machine Learning and Applications\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AI, Machine Learning and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/csit.2021.111304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AI, Machine Learning and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/csit.2021.111304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

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。
Research on Task Scheduling Strategy based on the Trustworthiness of MapReduce
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信