NeTS-NR ROSS.Net: A Platform for Integrated Large-Scale Network Design of Experiments and Simulation

NeTS-NR ROSS.Net：实验与仿真集成的大规模网络设计平台

• 批准号: 0435259
• 负责人: Christopher Carothers
• 金额: --
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0435259&HistoricalAwards=false
• 关键词: NeTS; NR; ROSS.Net; Platform; Integrated

National Science FoundationNETS - Research in Network Technologies and Systems CISE/CNSABSTRACTProposal Number: 0435259Principal Investigator: Kalyanaraman, ShivkumarInstitution: Rensselaer Polytechnic InstituteProposal Title: NeTS-NR ROSS.Net: A Platform for Integrated Large-Scale Net-work Design of Experiments and SimulationPerformance analysis tools to aid design, analysis, understanding and operation of networking protocols on large-scale and in heterogeneous deployment con-texts are urgently needed in networking research. Though there are popular tools for small-scale analysis and emerging test-bed facilities, large-scale analy-sis requires tools such as scalable simulators, experiment design and empirical modeling engines (a.k.a "meta-simulation" tools). The overall goal of this project is to provide tools that significantly improve the way networking community de-signs, tunes, and studies network protocols, especially for target deployment in large-scale, heterogeneous and time-varying conditions. In particular, the pro-ject develops an experimentation platform, called "ROSS.Net", with meta-simulation and simulation capabilities. In order to rapidly interpret system be-havior, ROSS.Net employs large-scale experiment design tools that allow model-ing and optimization of protocol response, i.e. a response surface in a large-dimensional parameter space. The goal is to generate a unified search, optimi-zation and sparse empirical modeling framework with demonstrated ability to pose meaningful large-scale design questions and provide "good" models rapidly for on-line operation. For a researcher to selectively compose a set of experi-ments resulting in accurate answers to the questions posed by the model de-signer; ROSS.Net uses reversible computation techniques to enable memory-efficient optimistic parallel simulation and model construction. The work has immediate impact in applications broadly in the area of computer systems where large-scale design is crucial (e.g. operating systems, distributed systems). Particularly, features like fast-approximation and sparse modeling have poten-tial impact in areas far from computer networking such as include industrial quality control, agriculture, and bioinformatics.Dr. Admela JukanProgram Director, CISE/CNSAug 5, 2004.

国家科学基金会NETS-网络技术和系统研究CISE/CNSABSTRACT提案编号：0435259主要研究员：Kalyanaraman，ShivanararInstitution：Rensselaer Polytechnic InstituteProposal Title：NetS-NR ROSS.Net：一个集成的大规模网络设计实验和仿真平台性能分析工具，以帮助设计，分析，在联网研究中迫切需要对大规模和异构部署环境中的联网协议的理解和操作。尽管有用于小规模分析和新兴测试台设施的流行工具，但大规模分析需要可扩展模拟器、实验设计和经验建模引擎（又名“元模拟”工具）等工具。该项目的总体目标是提供工具，显着改善网络社区设计，调整和研究网络协议的方式，特别是在大规模，异构和时变条件下的目标部署。特别是，该项目开发了一个实验平台，称为“ROSS.Net”，具有元仿真和仿真功能。为了快速解释系统的行为，ROSS.Net采用了大规模的实验设计工具，允许对协议响应进行建模和优化，即在一个大维度参数空间中的响应面。我们的目标是生成一个统一的搜索，优化和稀疏的经验建模框架，证明有能力提出有意义的大规模设计问题，并提供“好”的模型，迅速在线操作。对于研究人员来说，有选择地组成一组实验，从而准确回答模型设计者提出的问题; ROSS.Net使用可逆计算技术来实现内存高效的乐观并行模拟和模型构建。这项工作对计算机系统领域的应用有着直接的影响，其中大规模的设计是至关重要的（例如操作系统，分布式系统）。特别是，快速近似和稀疏建模等功能在远离计算机网络的领域具有潜在的影响，例如工业质量控制，农业和生物信息学。