基于仿真的云数据中心可扩展性、鲁棒性和复杂性的比较研究

M. F. Ali, O. Batarfi, A. Bashar
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引用次数: 2

摘要

本文提出了一种新的方法,对各种基于仿真的工具进行全面分析,以测试和测量云数据中心的性能、可扩展性、鲁棒性和复杂性。在云计算基础设施中有不同的云数据中心资源,如虚拟机、CPU、RAM、SAN、LAN和WAN拓扑。需要分析服务器机器在云计算中对客户的能源和服务的利用程度。我们使用CloudSim、CloudReports和Cloud Analyst工具分析了各种云资源。资源供应、云管理、负载平衡、健壮性和云可扩展性是本文讨论的主要工作范围。在这方面,给出了一些仿真测试结果和仿真,以便将它们与实时场景进行比较,从而引起我们对性能和可扩展性问题的注意,以指导未来的发展方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A simulation-based comparative study of Cloud Datacenter scalability, robustness and complexity
This, paper presents a novel approach towards a comprehensive analysis of various simulation-based tools to test and measure the Cloud Datacenter performance, scalability, robustness and complexity. There are different Cloud Datacenter resources in cloud Computing Infrastructure like Virtual Machine, CPU, RAM, SAN, LAN and WAN topologies. The server machines need to be analyzed for their extent of utilization in terms of energy and service to clients in cloud computing. We have analyzed various Cloud resources using CloudSim, CloudReports and Cloud Analyst tools. Resources provisioning, Cloud Management, Load Balancing, Robustness and Cloud Scalability are the primary scope of work discuss in this paper. In this regards some Simulation test results and Simulations are presented in order to compare them with real time scenario to bring the performance and scalability issues into our notice for future directions.
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