基于系统架构的云计算虚拟资源动态系统分配与应用

IF 1.1 Q3 COMPUTER SCIENCE, THEORY & METHODS Open Computer Science Pub Date : 2023-01-01 DOI:10.1515/comp-2022-0259
Chunhua Lin, Longzi Li, Yuanyi Chen
{"title":"基于系统架构的云计算虚拟资源动态系统分配与应用","authors":"Chunhua Lin, Longzi Li, Yuanyi Chen","doi":"10.1515/comp-2022-0259","DOIUrl":null,"url":null,"abstract":"Abstract Cloud computing is a system development method based on dynamic sharing, which allows a large number of systems to be combined to provide services. The purpose of this work is to study the design and implementation of a dynamic virtual resource allocation system in cloud computing, whose architecture allows load balancing between virtual resource pools and reduces resource wastage. Using the cluster network topology, the resource usage of the dynamic system cluster can be monitored in real time, and the total cluster load can be automatically determined based on the monitoring data. The experiment is divided into two parts. Performance testing and scenario testing. Performance tests examine execution time, processor, and memory performance. In the scenario test, JMeter is used to simulate the occurrence of a large number of concurrent application access requests, the loss rate, and processing time of these requests on the cloud platform, and load balancing tests are performed. The test results show that the system running time is about 22–27 ms, the CPU utilization is about 90–95%, and the RAM is about 3.5 ms. The results show that cloud technology can improve resource scheduling of large tasks and optimize resource load balance.","PeriodicalId":43014,"journal":{"name":"Open Computer Science","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic system allocation and application of cloud computing virtual resources based on system architecture\",\"authors\":\"Chunhua Lin, Longzi Li, Yuanyi Chen\",\"doi\":\"10.1515/comp-2022-0259\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Cloud computing is a system development method based on dynamic sharing, which allows a large number of systems to be combined to provide services. The purpose of this work is to study the design and implementation of a dynamic virtual resource allocation system in cloud computing, whose architecture allows load balancing between virtual resource pools and reduces resource wastage. Using the cluster network topology, the resource usage of the dynamic system cluster can be monitored in real time, and the total cluster load can be automatically determined based on the monitoring data. The experiment is divided into two parts. Performance testing and scenario testing. Performance tests examine execution time, processor, and memory performance. In the scenario test, JMeter is used to simulate the occurrence of a large number of concurrent application access requests, the loss rate, and processing time of these requests on the cloud platform, and load balancing tests are performed. The test results show that the system running time is about 22–27 ms, the CPU utilization is about 90–95%, and the RAM is about 3.5 ms. The results show that cloud technology can improve resource scheduling of large tasks and optimize resource load balance.\",\"PeriodicalId\":43014,\"journal\":{\"name\":\"Open Computer Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/comp-2022-0259\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/comp-2022-0259","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

摘要

云计算是一种基于动态共享的系统开发方法,它允许大量的系统组合起来提供服务。本工作的目的是研究云计算中动态虚拟资源分配系统的设计与实现,该系统的架构允许虚拟资源池之间的负载均衡,减少资源浪费。通过集群网络拓扑,可以实时监控动态系统集群的资源使用情况,并根据监控数据自动确定集群的总负载。实验分为两个部分。性能测试和场景测试。性能测试检查执行时间、处理器和内存性能。在场景测试中,使用JMeter模拟大量并发应用访问请求在云平台上的发生情况、丢失率和处理时间,并进行负载均衡测试。测试结果表明,系统运行时间约为22-27 ms, CPU利用率约为90-95%,RAM约为3.5 ms。结果表明,云技术可以改善大型任务的资源调度,优化资源负载平衡。
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
Dynamic system allocation and application of cloud computing virtual resources based on system architecture
Abstract Cloud computing is a system development method based on dynamic sharing, which allows a large number of systems to be combined to provide services. The purpose of this work is to study the design and implementation of a dynamic virtual resource allocation system in cloud computing, whose architecture allows load balancing between virtual resource pools and reduces resource wastage. Using the cluster network topology, the resource usage of the dynamic system cluster can be monitored in real time, and the total cluster load can be automatically determined based on the monitoring data. The experiment is divided into two parts. Performance testing and scenario testing. Performance tests examine execution time, processor, and memory performance. In the scenario test, JMeter is used to simulate the occurrence of a large number of concurrent application access requests, the loss rate, and processing time of these requests on the cloud platform, and load balancing tests are performed. The test results show that the system running time is about 22–27 ms, the CPU utilization is about 90–95%, and the RAM is about 3.5 ms. The results show that cloud technology can improve resource scheduling of large tasks and optimize resource load balance.
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
Open Computer Science
Open Computer Science COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
4.00
自引率
0.00%
发文量
24
审稿时长
25 weeks
期刊最新文献
Task offloading in mobile edge computing using cost-based discounted optimal stopping A Bi-GRU-DSA-based social network rumor detection approach Artificial intelligence-based public safety data resource management in smart cities Application of fingerprint image fuzzy edge recognition algorithm in criminal technology Application of SSD network algorithm in panoramic video image vehicle detection system
×
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