EAGER: Thin Client Performance Benchmarking based Resource Adaptation in Virtual Desktop Clouds

EAGER：虚拟桌面云中基于瘦客户端性能基准的资源适应

• 批准号: 1342499
• 负责人: Prasad Calyam
• 金额: $ 4.17万
• 依托单位: University of Missouri-Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1342499&HistoricalAwards=false
• 关键词: EAGER; Thin; Client; Performance; Benchmarking

Popular applications such as email, image/video galleries, and file storage are increasingly being supported by ?cloud? platforms in residential, academia and industry communities. The next frontier for these user communities will be to transition ?traditional desktops? that have dedicated hardware and software configurations into ?virtual desktop clouds? that are accessible via thin clients. This project aims to develop optimal resource allocation frameworks and performance benchmarking tools that can enable building and managing thin-client based virtual desktop clouds at Internet-scale. Virtual desktop cloud experiments under realistic user and system loads will be conducted by leveraging multiple kinds of GENI resources such as aggregates, user opt-in mechanisms, measurement services and experimenter workflow tools. Project outcomes will help in minimizing costly cloud resource over-commitment, and in avoiding thin client protocol configuration guesswork, while delivering optimum user experience. Further, they will positively impact computer desktop user communities, GENI-like testbeds, and equipment vendors.

电子邮件、图像/视频库和文件存储等流行应用程序越来越多地受到云计算的支持。住宅、学术和工业社区的平台。这些用户社区的下一个前沿将是过渡？传统桌面？将专用硬件和软件配置整合到虚拟桌面云中？可通过瘦客户机访问。该项目旨在开发优化资源分配框架和性能基准工具，以支持在互联网范围内构建和管理基于瘦客户机的虚拟桌面云。将利用聚合、用户选择加入机制、测量服务和实验者工作流工具等多种Geni资源，在现实用户和系统负载下进行虚拟桌面云实验。项目成果将有助于最大限度地减少昂贵的云资源过量使用，并避免瘦客户端协议配置猜测，同时提供最佳用户体验。此外，它们将对计算机桌面用户社区、精灵般的试验台和设备供应商产生积极影响。