Collaborative Research: Frameworks for NS-3

该项目正在为ns-3离散事件网络仿真器开发新的仿真框架，ns-3离散事件网络仿真器是一个免费的开源研究工具，专为计算机通信网络研究人员设计。模拟因其易用性、重复性、可用性、可扩展性和软件开发的简易性而在网络研究和教育中得到广泛应用。然而，典型模拟研究的工作流程需要用户仔细注意方法学上的一些最佳做法，以确保结果可信且可由第三方重现，并且不会引入错误。该项目正在为ns-3模拟器建立一个自动化框架，以提供一个更有利于创建严谨研究的环境。该自动化框架通过合成和一致性检查以及实验设置的定义来指导用户生成有效的网络仿真模型。该框架对大规模模拟研究实施控制，并应用统计方法进行输出数据分析和执行控制。该框架还收集复制实验和报告结果所需的细节。该框架还允许用户指定广泛的模拟网络拓扑、应用流量和其他参数，从而允许以最小的努力在广泛的场景中进行实验。最后，继续维护ns-3软件、文件和传播活动。作为开源软件传播的ns-3的补充，正在改进未来基于模拟的网络研究的方法和可信度。

This project is developing new simulation frameworks for the ns-3 discrete-event network simulator, a free and open-source research tool designed for use by computer communications network researchers. Simulation remains in heavy use for network research and education, because of its ease of use, reproducibility, availability, scalability, and ease of software development. However, the workflow of a typical simulation study requires the user's careful attention to a number of best practices in methodology to ensure that the results are credible and reproducible by third parties and that errors are not introduced. This project is building an automation framework for the ns-3 simulator that provides an environment that is more conducive to the creation of rigorous studies. The automation framework guides the user to produce valid network simulation models by composition and consistency checking, and definition of experimental settings. The framework exercises control over large-scale simulation studies, and applies statistical methods for output data analysis and execution control. The framework also collect details required to reproduce the experiment and report results. The framework also allows users to specify wide ranges of simulation network topologies, application traffic, and other parameters, allowing experiments to be conducted on a wide range of scenarios with minimal effort. Finally, maintaining the ns-3 software, documentation, and dissemination activities continue. The additions to ns-3, disseminated as open source software, are improving the methodology and credibility for future simulation-based network research.