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

国家科学基金NETS-网络技术与系统研究CESE/CNSABSTRACT论文编号：0435259论文编号：0435259论文编号：0435259论文作者：Kalyanaraman，Shivkumar研究所：伦斯勒理工学院论文题目：NETS-NR ROSS.Net：一个集成的大型网络实验与仿真设计平台在网络研究中迫切需要性能分析工具来辅助设计、分析、理解和操作大规模和异质部署环境下的网络协议。虽然有流行的小规模分析工具和新兴的试验台设施，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(又称元模拟工具)等工具。该项目的总体目标是提供工具，显著改进网络社区设计、调整和研究网络协议的方式，特别是在大规模、异类和时变条件下的目标部署。具体来说，本课题开发了一个具有元仿真和仿真能力的实验平台--ROSS.Net。为了快速解释系统行为，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，即在高维参数空间中的响应面。其目标是生成一个统一的搜索、优化和稀疏经验建模框架，该框架具有提出有意义的大规模设计问题的能力，并为在线操作快速提供“好的”模型。为了研究人员有选择地组成一组实验，从而准确地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。这项工作在大规模设计至关重要的计算机系统领域(例如操作系统、分布式系统)的广泛应用中具有立竿见影的影响。特别是，快速逼近和稀疏建模等特征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。Admela Jukan项目主任，CEISE/CNS2004年8月5日。

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.