基于CLARA和进化范式的Cloudlet和虚拟机性能增强

Tanvi Gupta, Supriya P. Panda
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引用次数: 3

摘要

标准化的IT范例将服务汇集在一起,形成一个互联网网络,这就是云计算。因此,云提供商在这一点上管理负载是困难的,因此体现了负载平衡概念的存在。该算法的目标是通过最小化结果(包括执行时间、Makespan时间和处理成本)和最大化吞吐量来提高性能,并使用ABC优化。算法使用R代码执行,数据集使用Microsoft Excel 2007进行处理。数据集中虚拟机的MIPS值为2000 ~ 9000,带宽值为10000 ~ 50000。最后得出结论:3个集群的执行时间、最大完成时间和处理成本的效率在18% ~ 20%之间,吞吐量和不平衡程度分别约为16%和6%;对于10个集群,执行时间和完工时间的效率提高到大约50%,处理成本、吞吐量和不平衡程度分别提高到大约72%、33%和4%。
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Cloudlet and Virtual Machine Performance Enhancement With CLARA and Evolutionary Paradigm
The standardised IT paradigm pools services together as an internet network is cloud computing. So, management of the load by cloud providers at this point is difficult and hence manifests the existence of load balancing concept. The aim of proposed algorithm is to enhance the performance by minimizing results, which includes Execution time, Makespan time, and Processing Cost, and maximizing throughput, using ABC Optimization. R code is used to execute the algorithm, and dataset is processed using Microsoft Excel 2007. In the dataset, the MIPS of VMs range from 2000-9000 and bandwidth range from 10000-50000. Finally, it is concluded that, for 3 clusters, the efficiency rate of execution time, makespan time, and processing cost lies between 18%-20% and throughput and degree of imbalance are approximately 16% and 6%, respectively, when compared with the previous work; and for 10 clusters, the efficiency rate of execution time and makespan time raises to approximately 50% with processing cost, throughput, and degree of imbalance as approximately 72%, 33%, and 4%, respectively.
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