CAREER: Immersive Large-Scale Network Simulations

职业：沉浸式大规模网络模拟

• 批准号: 0836408
• 负责人: Jason Liu
• 金额: $ 33.68万
• 依托单位: Florida International University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-05-15 至 2012-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0836408&HistoricalAwards=false
• 关键词: CAREER; Immersive; Large; Scale; Network

The success of advancing technologies critical to designing future-generation high-performance global networks and reliable distributed applications hinges on the available tools that can effectively prototype test, and analyze new ideas. The project will enable advances in the area of high-performance modeling and simulation of large-scale networks. The research includes an investigation of the fundamental technologies that enable real-time large-scale network simulationsand the development of a real-time immersive network simulation environment. Real-time network simulation combines the advantages of both simulation and emulation by running simulation models that interact with the physical world. Immersive large-scale network simulation requires that the simulation not only capture important characteristics of the target global network, but also support seamless interactions with distributed applications in real time. The project is divided into three research thrusts: imprecise simulation, GPU co-simulation, and the development of the immersive network simulation environment. Imprecise simulation, extended from the imprecise computation technique originally designed for real-time systems, aims to achieve real-time performance of large-scale network simulations, by allowing the simulation to choose among models with different modeling representations and with variable computing requirements during run-time. GPU co-simulation exploits the computing resource of graphics processors, which are almost omnipresent on todays desktop computers and become more powerful than CPUs; certain numerical computations, such as the network background traffic calculation, can be offloaded to the graphics hardware, so that the CPUs can concentrate on more critical tasks for real-time simulation. An immersive network simulation environment will be developed based on the imprecise simulation and GPU co-simulation techniques, and will also include models of network protocols of alternative designs of the layered network structures.

对于设计下一代高性能全球网络和可靠的分布式应用程序至关重要的先进技术的成功取决于能够有效进行原型测试和分析新想法的可用工具。该项目将推动大规模网络高性能建模和仿真领域的进步。该研究包括对实现实时大规模网络仿真的基础技术的调查以及实时沉浸式网络仿真环境的开发。实时网络仿真通过运行与物理世界交互的仿真模型，结合了仿真和仿真的优点。沉浸式大规模网络仿真要求仿真不仅捕获目标全局网络的重要特征，而且支持与分布式应用程序的实时无缝交互。 该项目分为三个研究重点：不精确仿真、GPU联合仿真以及沉浸式网络仿真环境的开发。不精确仿真是从最初为实时系统设计的不精确计算技术延伸出来的，旨在通过允许仿真在运行时选择具有不同建模表示和可变计算需求的模型来实现大规模网络仿真的实时性能。 GPU 协同仿真利用了图形处理器的计算资源，图形处理器在当今的台式计算机上几乎无处不在，并且变得比 CPU 更强大；某些数值计算，例如网络后台流量计算，可以卸载到图形硬件，以便CPU可以专注于更关键的任务进行实时模拟。基于不精确仿真和GPU联合仿真技术，将开发沉浸式网络仿真环境，并且还将包括分层网络结构的替代设计的网络协议模型。