云计算环境下任务调度算法的相关研究

Syed Arshad Ali, Mansaf Alam
{"title":"云计算环境下任务调度算法的相关研究","authors":"Syed Arshad Ali, Mansaf Alam","doi":"10.1109/IC3I.2016.7917943","DOIUrl":null,"url":null,"abstract":"Cloud Computing is a paradigm of both parallel processing and distributed computing. It offers computing facilities as a utility service in pay as par use manner. Virtualization, self-service provisioning, elasticity and pay per use are the key features of Cloud Computing. It provides different types of resources over the Internet to perform user submitted tasks. In cloud environment, huge number of tasks are executed simultaneously, an effective Task Scheduling is required to gain better performance of the cloud system. Various Cloud-based Task Scheduling algorithms are available that schedule the user's task to resources for execution. Due to the novelty of Cloud Computing, traditional scheduling algorithms cannot satisfy the cloud's needs, the researchers are trying to modify traditional algorithms that can fulfil the cloud requirements like rapid elasticity, resource pooling and on-demand self-service. In this paper the current state of Task Scheduling algorithms has been discussed and compared on the basis of various scheduling parameters like execution time, throughput, makespan, resource utilization, quality of service, energy consumption, response time and cost.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"A relative study of task scheduling algorithms in cloud computing environment\",\"authors\":\"Syed Arshad Ali, Mansaf Alam\",\"doi\":\"10.1109/IC3I.2016.7917943\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud Computing is a paradigm of both parallel processing and distributed computing. It offers computing facilities as a utility service in pay as par use manner. Virtualization, self-service provisioning, elasticity and pay per use are the key features of Cloud Computing. It provides different types of resources over the Internet to perform user submitted tasks. In cloud environment, huge number of tasks are executed simultaneously, an effective Task Scheduling is required to gain better performance of the cloud system. Various Cloud-based Task Scheduling algorithms are available that schedule the user's task to resources for execution. Due to the novelty of Cloud Computing, traditional scheduling algorithms cannot satisfy the cloud's needs, the researchers are trying to modify traditional algorithms that can fulfil the cloud requirements like rapid elasticity, resource pooling and on-demand self-service. In this paper the current state of Task Scheduling algorithms has been discussed and compared on the basis of various scheduling parameters like execution time, throughput, makespan, resource utilization, quality of service, energy consumption, response time and cost.\",\"PeriodicalId\":305971,\"journal\":{\"name\":\"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC3I.2016.7917943\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3I.2016.7917943","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

摘要

云计算是并行处理和分布式计算的典范。它以按价付费的方式提供计算设施作为公用事业服务。虚拟化、自助服务、弹性和按次付费是云计算的关键特性。它通过Internet提供不同类型的资源来执行用户提交的任务。在云环境中,大量任务同时执行,需要有效的任务调度来获得更好的云系统性能。可以使用各种基于云的任务调度算法,将用户的任务调度到资源中执行。由于云计算的新颖性,传统的调度算法无法满足云的需求,研究人员正在尝试修改传统的算法,以满足云的需求,如快速弹性、资源池和按需自助服务。本文从执行时间、吞吐量、makespan、资源利用率、服务质量、能耗、响应时间和成本等调度参数出发,对任务调度算法的现状进行了讨论和比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A relative study of task scheduling algorithms in cloud computing environment
Cloud Computing is a paradigm of both parallel processing and distributed computing. It offers computing facilities as a utility service in pay as par use manner. Virtualization, self-service provisioning, elasticity and pay per use are the key features of Cloud Computing. It provides different types of resources over the Internet to perform user submitted tasks. In cloud environment, huge number of tasks are executed simultaneously, an effective Task Scheduling is required to gain better performance of the cloud system. Various Cloud-based Task Scheduling algorithms are available that schedule the user's task to resources for execution. Due to the novelty of Cloud Computing, traditional scheduling algorithms cannot satisfy the cloud's needs, the researchers are trying to modify traditional algorithms that can fulfil the cloud requirements like rapid elasticity, resource pooling and on-demand self-service. In this paper the current state of Task Scheduling algorithms has been discussed and compared on the basis of various scheduling parameters like execution time, throughput, makespan, resource utilization, quality of service, energy consumption, response time and cost.
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
期刊最新文献
Single-resistance-controlled quadrature oscillator employing two current differencing buffered amplifier FMODC: Fuzzy guided multi-objective document clustering by GA A study on disruption tolerant session based mobile architecture How effective is Black Hole Algorithm? Design of a high gain 16 element array of microstrip patch antennas for millimeter wave applications
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1