基于排队论的云计算中心性能分析模型

Zhang Yong-hua, Zhou Zhen, Zeng Fan-zi, Li Yuan
{"title":"基于排队论的云计算中心性能分析模型","authors":"Zhang Yong-hua, Zhou Zhen, Zeng Fan-zi, Li Yuan","doi":"10.2174/1874444301507012280","DOIUrl":null,"url":null,"abstract":"To make comprehensive and objective analysis of the performance of the cloud computing system center, a cloud computing center system analysis model based on queuing theory is proposed. First, to describe the characteristics of user's service changes request arrived at center by using Poisson distribution, the batch arrival system model was estab- lished based on queuing theory, then solve the steady-state probability of length on the probability space, finally to ana- lyze the performance indexes as blocking probability, prompt service probability, etc. by using simulation experiment. The simulation results indicate that with increased batch arrival requests, the average length of the cloud computing center increases correspondingly. Increasing the length of the buffer can reduce the blocking probability of system, the experi- mental results can provide valuable reference for cloud service providers. Cloud computing system is a kind of data processing center that takes Internet as the core. Unified schedule stor- age, software, services and other resources, constitute a vir- tual computer center, to provide users with on-demand busi- ness model. Due to the increasing species of user demand, the users put forward requests of higher service quality of cloud computing system center. Cloud computing center is the core of the cloud computing system, the advantages and disadvantages of whose performance directly determine the pros and cons of cloud computing service quality, thus make the comprehensive and accurate analysis of the performance of cloud computing system center of great significance (1, 2). For the analysis of cloud computing system center, do- mestic and foreign scholars, and experts have invested a lot of time and energy to conduct a wide range of research; a lot of cloud computing center performance models came to the fore. Traditional cloud computing center performance analy- sis models adopt the simulation system such as the realiza- tion of CloudSim , they belong to the kind of static analysis model, assuming that cloud computing system center is op- erating at static state. However, in practical applications, cloud computing systems center has large scale and complex structure, and with time-dependent nature and mutability, it is difficult to establish accurate analysis model by using tradi- tional model. In order to solve the shortage of the traditional model, this paper proposes center analysis model of cloud computing system based on the data aggregation algorithm,","PeriodicalId":153592,"journal":{"name":"The Open Automation and Control Systems Journal","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The Cloud Computing Center Performance Analysis Model Based onQueuing Theory\",\"authors\":\"Zhang Yong-hua, Zhou Zhen, Zeng Fan-zi, Li Yuan\",\"doi\":\"10.2174/1874444301507012280\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To make comprehensive and objective analysis of the performance of the cloud computing system center, a cloud computing center system analysis model based on queuing theory is proposed. First, to describe the characteristics of user's service changes request arrived at center by using Poisson distribution, the batch arrival system model was estab- lished based on queuing theory, then solve the steady-state probability of length on the probability space, finally to ana- lyze the performance indexes as blocking probability, prompt service probability, etc. by using simulation experiment. The simulation results indicate that with increased batch arrival requests, the average length of the cloud computing center increases correspondingly. Increasing the length of the buffer can reduce the blocking probability of system, the experi- mental results can provide valuable reference for cloud service providers. Cloud computing system is a kind of data processing center that takes Internet as the core. Unified schedule stor- age, software, services and other resources, constitute a vir- tual computer center, to provide users with on-demand busi- ness model. Due to the increasing species of user demand, the users put forward requests of higher service quality of cloud computing system center. Cloud computing center is the core of the cloud computing system, the advantages and disadvantages of whose performance directly determine the pros and cons of cloud computing service quality, thus make the comprehensive and accurate analysis of the performance of cloud computing system center of great significance (1, 2). For the analysis of cloud computing system center, do- mestic and foreign scholars, and experts have invested a lot of time and energy to conduct a wide range of research; a lot of cloud computing center performance models came to the fore. Traditional cloud computing center performance analy- sis models adopt the simulation system such as the realiza- tion of CloudSim , they belong to the kind of static analysis model, assuming that cloud computing system center is op- erating at static state. However, in practical applications, cloud computing systems center has large scale and complex structure, and with time-dependent nature and mutability, it is difficult to establish accurate analysis model by using tradi- tional model. In order to solve the shortage of the traditional model, this paper proposes center analysis model of cloud computing system based on the data aggregation algorithm,\",\"PeriodicalId\":153592,\"journal\":{\"name\":\"The Open Automation and Control Systems Journal\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Open Automation and Control Systems Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/1874444301507012280\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Open Automation and Control Systems Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1874444301507012280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

为了全面客观地分析云计算系统中心的性能,提出了一种基于排队论的云计算中心系统分析模型。首先利用泊松分布描述用户服务变更请求到达中心的特征,建立基于排队论的批量到达系统模型,然后在概率空间上求解长度的稳态概率,最后通过仿真实验分析阻塞概率、提示服务概率等性能指标。仿真结果表明,随着批量到达请求的增加,云计算中心的平均长度也相应增加。增加缓冲区长度可以降低系统的阻塞概率,实验结果可以为云服务提供商提供有价值的参考。云计算系统是一种以互联网为核心的数据处理中心。统一调度存储、软件、服务等资源,构成虚拟计算机中心,为用户提供按需的商业模式。随着用户需求种类的不断增加,用户对云计算系统中心的服务质量提出了更高的要求。云计算中心是云计算系统的核心,其性能的优劣直接决定了云计算服务质量的优劣,因此对云计算系统中心的性能进行全面、准确的分析具有重要意义(1,2)。对于云计算系统中心的分析,国内外学者、专家投入了大量的时间和精力进行了广泛的研究;许多云计算中心性能模型出现了。传统的云计算中心性能分析模型采用CloudSim等仿真系统实现,属于静态分析模型,假设云计算系统中心在静态状态下运行。然而,在实际应用中,云计算系统中心规模大、结构复杂,且具有时间依赖性和可变性,利用传统模型难以建立准确的分析模型。为了解决传统模型的不足,本文提出了基于数据聚合算法的云计算系统中心分析模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Cloud Computing Center Performance Analysis Model Based onQueuing Theory
To make comprehensive and objective analysis of the performance of the cloud computing system center, a cloud computing center system analysis model based on queuing theory is proposed. First, to describe the characteristics of user's service changes request arrived at center by using Poisson distribution, the batch arrival system model was estab- lished based on queuing theory, then solve the steady-state probability of length on the probability space, finally to ana- lyze the performance indexes as blocking probability, prompt service probability, etc. by using simulation experiment. The simulation results indicate that with increased batch arrival requests, the average length of the cloud computing center increases correspondingly. Increasing the length of the buffer can reduce the blocking probability of system, the experi- mental results can provide valuable reference for cloud service providers. Cloud computing system is a kind of data processing center that takes Internet as the core. Unified schedule stor- age, software, services and other resources, constitute a vir- tual computer center, to provide users with on-demand busi- ness model. Due to the increasing species of user demand, the users put forward requests of higher service quality of cloud computing system center. Cloud computing center is the core of the cloud computing system, the advantages and disadvantages of whose performance directly determine the pros and cons of cloud computing service quality, thus make the comprehensive and accurate analysis of the performance of cloud computing system center of great significance (1, 2). For the analysis of cloud computing system center, do- mestic and foreign scholars, and experts have invested a lot of time and energy to conduct a wide range of research; a lot of cloud computing center performance models came to the fore. Traditional cloud computing center performance analy- sis models adopt the simulation system such as the realiza- tion of CloudSim , they belong to the kind of static analysis model, assuming that cloud computing system center is op- erating at static state. However, in practical applications, cloud computing systems center has large scale and complex structure, and with time-dependent nature and mutability, it is difficult to establish accurate analysis model by using tradi- tional model. In order to solve the shortage of the traditional model, this paper proposes center analysis model of cloud computing system based on the data aggregation algorithm,
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:604180095
Book学术官方微信