ANI/STI: Measurements, Models, and Simulation Scenarios for Internet Research

网络研究人员从互联网重要属性的心理模型中工作。在模拟和实验中使用的场景揭示了这些心理模型的各个方面，通常包括以下一个或多个：(1)流存在很长时间并传输大量数据。简单的拓扑，如“哑铃”拓扑，只有一条拥塞链路，足以研究许多交通特性(2)拥塞链路上的流量共享小范围的往返时间(3)大多数跨链路的流量是单向的(4)反向路径流量很少堵塞。所有这些模型都可以深刻影响仿真和实验结果，因此对研究的评价，但没有一个被测量研究证实，有些是积极错误的。一些与现实的偏差并不重要，因为它们不会影响模拟结果的有效性，简单的模型有助于人们理解系统的潜在动力学。然而，作为一个社区，我们还不了解模型的哪些方面影响基本的系统行为，哪些方面可以被安全地忽略。该项目建议建立对现实网络模型范围的更丰富的理解，以及不同模型参数与网络性能的可能相关性。缺乏良好的测量，缺乏评估测量结果并将其结果应用于模型的工具，以及缺乏基于这些模型的多样化和易于理解的模拟场景，这些都阻碍了该领域的发展。该计划将直接解决网络研究人员在模拟和实验中使用的模型。建立在现有测量结果的基础上，并在需要的地方产生新的经验结果，这将创造高质量的工具，以促进该小组和更广泛的网络研究社区正在进行的测量，从而使结果跟上互联网的高速变化。综合相关的测量结果将提供简洁的直觉，以及一系列可供研究人员使用的模拟模型。将举例说明模型的各个方面如何影响模拟和实验。这项工作不会创造一个全球互联网的通用模式（一个巨大而不必要的事业）。相反，它将专注于研究人员在特定研究领域使用的模型，以解决他们紧迫的建模问题。首先专注于小组自己的专业领域，特别是在路由器队列中建模拥塞相关机制，后来解决其他研究领域，帮助他人改进他们的测量和测量工具，以及由此产生的模型和仿真场景，并改善实验，模型之间的关系，以及我们对仿真结果的共同理解。

Networking researchers work from mental models of the Internet's important properties. The scenarios used in simulations and experiments reveal aspects of these mental models, often including one or more of the following: (1) Flows live for a long time and transfer a lot of data. Simple topologies, like the "dumbbell" topology, with one congested link, are sufficient to study many traffic properties(2) Flows on the congested link share a small range of round-trip times(3) Most traffic across the link is one-way (4) Reverse-path traffic is rarely congestedAll of these models can deeply affect simulation and experimental results, and therefore evaluations of research, but none of them are confirmed by measurement studies, and some are actively wrong. Some divergences from reality are unimportant, in that they don't affect the validity of simulation results, and simple models help people understand the underlying dynamics of systems. However, as a community we do not yet understand which aspects of models affect fundamental system behavior, and which aspects can safely be ignored. This project proposes to build a much richer understanding of the range of realistic network models, and of the likely relevance of different model parameters to network performance. The lack of good measurements, lack of tools for evaluating measurement results and applying their results to models, and lack of diverse and well-understood simulation scenarios based on these models, are holding back the field. This program will directly address the models used by network researchers in simulations and experiments. Building on the wealth of existing measurement results and generating new empirical results where needed, this will create high-quality tools to facilitate ongoing measurement by this group and the wider network research community, so that the results keep up with the Internet's high rate of change. Synthesizing the relevant body of measurement results will provide concise intuitions, and a range of simulation-ready models, for use by researchers. An illustration of how each aspect of the models can influence simulations and experiments will be given.This work will not create a universal model of the global Internet (an immense and unnecessary undertaking). Instead, it will focus on models used by researchers in specific research areas, motivated by addressing their pressing modeling concerns. Focusing at first on the group's own areas of expertise, particularly modeling congestion-related mechanisms at a queue in a router, and later address other research areas, help others improve their measurements and measurement tools, along with the resulting models and simulation scenarios, and improve the relationships between experiments, models, and our shared understanding of simulation results.