云计算中虚拟机迁移方法的设计与实现

Q4 Mathematics Philippine Statistician Pub Date : 2022-07-19 DOI:10.17762/msea.v71i3s.14
Shubhashish Goswami, Digvijay Singh, Sachin Sharma
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引用次数: 0

摘要

云是一种通信体系结构,包括虚拟机、数据中心、主机和代理。对于cloudlet执行,代理程序会寻找最可靠的虚拟机。网络中可能会出现哪个系统过载的不确定性。本文提出了一种提高系统容错性的工作技术。所提出的增强基于ACO算法,该算法可以确定将cloudlet迁移到的最佳虚拟机。正在Cloudsim上评估所提出算法的执行时间和能耗性能。与TESA相比,仿真结果表明,蚁群优化算法(ACO)运行时间和精力最少(三步加密算法)。所提出的算法可以用于云计算中的负载平衡。
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Design and Implementation of Virtual Machine Migration Method in Cloud Computing
The cloud is a communication architecture that includes virtual machines, data centers, hosts, and brokers. For cloudlet execution, the broker looks for the most reliable virtual machine. Uncertainty may arise in the network as to which system is overloaded. A work technique is proposed in this study to improve the system's fault tolerance. The proposed enhancement is based on the ACO algorithm, which can determine the best virtual machine to migrate a cloudlet to. The proposed algorithm's performance is being evaluated on Cloudsim in terms of execution time and energy consumption. When compared to TESA, the simulation results showed that ACO (Ant Colony Optimization) takes the least amount of time and energy to run (Three Step Encryption Algorithm). The proposed algorithm can be used in cloud computing for load balancing.
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来源期刊
Philippine Statistician
Philippine Statistician Mathematics-Statistics and Probability
CiteScore
0.50
自引率
0.00%
发文量
92
期刊介绍: The Journal aims to provide a media for the dissemination of research by statisticians and researchers using statistical method in resolving their research problems. While a broad spectrum of topics will be entertained, those with original contribution to the statistical science or those that illustrates novel applications of statistics in solving real-life problems will be prioritized. The scope includes, but is not limited to the following topics:  Official Statistics  Computational Statistics  Simulation Studies  Mathematical Statistics  Survey Sampling  Statistics Education  Time Series Analysis  Biostatistics  Nonparametric Methods  Experimental Designs and Analysis  Econometric Theory and Applications  Other Applications
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