基于WFPSO算法的云虚拟机放置策略
随着云计算技术的大规模应用，云应用的交互更加依赖于网络，较差网络拓扑的选择增加了应用在网络中的通信流量，严重影响应用的运行效率和服务质量。为解决此问题，提出了一种基于粒子群优化算法的虚拟机放置策略。该策略通过建立云环境内部时延模型，利用改进的粒子群优化算法求解目标函数来降低应用的时延，提高运行效率。在CloudSim平台上进行仿真实验，结果表明，该策略的响应时间低于基本粒子群优化算法（PSO），并且修改后的PSO算法在不影响收敛精度的前提下较大幅度地提高了粒子群算法的收敛速度和云环境中应用的运行效率。...
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| Published in | 计算机应用研究 Vol. 34; no. 2; pp. 591 - 594 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
南京邮电大学计算机学院,南京,210046%中兴通讯股份有限公司,南京,210012
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2017.02.060 |
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| Abstract | 随着云计算技术的大规模应用，云应用的交互更加依赖于网络，较差网络拓扑的选择增加了应用在网络中的通信流量，严重影响应用的运行效率和服务质量。为解决此问题，提出了一种基于粒子群优化算法的虚拟机放置策略。该策略通过建立云环境内部时延模型，利用改进的粒子群优化算法求解目标函数来降低应用的时延，提高运行效率。在CloudSim平台上进行仿真实验，结果表明，该策略的响应时间低于基本粒子群优化算法（PSO），并且修改后的PSO算法在不影响收敛精度的前提下较大幅度地提高了粒子群算法的收敛速度和云环境中应用的运行效率。 |
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| AbstractList | TN915.05; 随着云计算技术的大规模应用,云应用的交互更加依赖于网络,较差网络拓扑的选择增加了应用在网络中的通信流量,严重影响应用的运行效率和服务质量.为解决此问题,提出了一种基于粒子群优化算法的虚拟机放置策略.该策略通过建立云环境内部时延模型,利用改进的粒子群优化算法求解目标函数来降低应用的时延,提高运行效率.在CloudSim平台上进行仿真实验,结果表明,该策略的响应时间低于基本粒子群优化算法(PSO),并且修改后的PSO算法在不影响收敛精度的前提下较大幅度地提高了粒子群算法的收敛速度和云环境中应用的运行效率. 随着云计算技术的大规模应用，云应用的交互更加依赖于网络，较差网络拓扑的选择增加了应用在网络中的通信流量，严重影响应用的运行效率和服务质量。为解决此问题，提出了一种基于粒子群优化算法的虚拟机放置策略。该策略通过建立云环境内部时延模型，利用改进的粒子群优化算法求解目标函数来降低应用的时延，提高运行效率。在CloudSim平台上进行仿真实验，结果表明，该策略的响应时间低于基本粒子群优化算法（PSO），并且修改后的PSO算法在不影响收敛精度的前提下较大幅度地提高了粒子群算法的收敛速度和云环境中应用的运行效率。 |
| Abstract_FL | With the large-scale application of cloud computing technology,the interaction of cloud applications more dependent on the network,a poor network topology would increase the network traffic of application,seriously affected the application of the operation efficiency and service quality.In order to solve this problem,this paper presented a virtual machine deployment strategy based on particle swarm optimization algorithm.This strategy used the improved particle swarm optimization algorithm to solve the objective function,and reduced the time delay to improve the operating efficiency.This paper gave the simulation experiment on CloudSim platform.And the results show that response time the strategy of is less than basic particle swarm optimization algorithm(PSO),and the modified PSO algorithm can improve the convergence speed of the particle swarm optimization,and improve the operating efficiency of the cloud environment. |
| Author | 何利文 袁野 王延松 呼学理 牛小兵 |
| AuthorAffiliation | 南京邮电大学计算机学院,南京210046 中兴通讯股份有限公司,南京210012 |
| AuthorAffiliation_xml | – name: 南京邮电大学计算机学院,南京,210046%中兴通讯股份有限公司,南京,210012 |
| Author_FL | Yuan Ye He Liwen Hu Xueli Wang Yansong Niu Xiaobing |
| Author_FL_xml | – sequence: 1 fullname: He Liwen – sequence: 2 fullname: Yuan Ye – sequence: 3 fullname: Wang Yansong – sequence: 4 fullname: Hu Xueli – sequence: 5 fullname: Niu Xiaobing |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitleAlternate | Placement strategy of cloud virtual machine based on WFPSO algorithm |
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| Keywords | time delay 粒子群优化算法 virtual machine placement 时延 particle swarm optimization algorithm 虚拟机放置 |
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| Notes | 51-1196/TP He Liwen1, Yuan Ye1, Wang Yansong2, Hu Xueli2, Niu Xiaobing2（ 1. School of Computer Science ＆ Technology, Nanjing University of Posts ＆ Telecommunications, Nanjing 210046, China; 2. Zhongxing Telecommunication Equipment Corporation, Nanjing 210012, China） particle swarm optimization algorithm; virtual machine placement; time delay With the large-scale application of cloud computing technology, the interaction of cloud applications more depen- dent on the network, a poor network topology would increase the network traffic of application, seriously affected the application of the operation efficiency and service quality. In order to solve this problem, this paper presented a virtual machine deployment strategy based on particle swarm optimization algorithm. This strategy used the improved particle swarm optimization algorithm to solve the objective function, and reduced the time delay to improve the operating efficiency. This paper gave the simulation experiment on CloudSim platform. And the results sho |
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| PublicationTitle | 计算机应用研究 |
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| PublicationYear | 2017 |
| Publisher | 南京邮电大学计算机学院,南京,210046%中兴通讯股份有限公司,南京,210012 |
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| Snippet | 随着云计算技术的大规模应用，云应用的交互更加依赖于网络，较差网络拓扑的选择增加了应用在网络中的通信流量，严重影响应用的运行效率和服务质量。为解决此问题，提出了一... TN915.05; 随着云计算技术的大规模应用,云应用的交互更加依赖于网络,较差网络拓扑的选择增加了应用在网络中的通信流量,严重影响应用的运行效率和服务质量.为解决此问题,提... |
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| SubjectTerms | 时延 粒子群优化算法 虚拟机放置 |
| Title | 基于WFPSO算法的云虚拟机放置策略 |
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