Large-Scale Computer Network Experimentation Through Simulation

计算机网络的研究虽然是一门相对年轻的科学，但与任何科学探究没有什么不同，因此需要建立在理论验证的基础之上。 在这个奖项中，我们专注于使用基于计算机的模拟，它提供了最大的灵活性，在创建一个通用的实验环境。 然而，模拟提供了几个重要的挑战。 首先，互联网是一个不断变化的、高度异构的环境，通常很难建模。 第二个问题是如何在基于计算机的模拟中忠实地反映互联网的大规模。 我们主要感兴趣的是在这项研究中解决后一个挑战。 我们对大规模网络仿真的兴趣是出于这样一个事实，即我们认为网络仿真是一种重要的工具，可以用来了解新协议、机制、网络服务或应用程序在大型网络（如Internet）上广泛部署时的真实效果。 简单地扩展从小规模模拟得出的结论并在扩展到大规模时对效果和行为进行推断显然是有问题的。虽然在互联网规模的网络模拟今天仍然是不可行的，但在过去几年中，在提高网络模拟的规模能力方面取得了相当大的进展。 我们的工作使用这种改进的扩展能力作为起点。 该奖项代表了超越如何执行大规模模拟运行的问题并解决如何执行大规模模拟实验的问题的努力。 模拟实验通常由多个相关运行组成，并且还由特定的验证和/或评估目标（例如，如果ISP在其所有路由器中启用某个队列管理算法，将会发生什么）。 我们注意到，我们的工作主要集中在包级离散事件模拟，而不是其他方法，允许通过聚合和近似缩放。 我们的目标是了解忠实的数据包级离散事件仿真的限制，作为一个车辆的实验和validation.With调查的问题，如何进行大规模的仿真实验的目标，我们集中在两个主要的研究领域：1。 我们将开发和分析允许多个网络模拟运行的有效执行的技术。一个关键的观察是，组成实验的多次运行通常是相关的。 利用这一事实，我们将开发技术，允许从一个运行的计算在其他运行中重用，从而减少了时间来完成一组运行。我们的初步工作证明了这种方法的可行性。我们注意到，虽然我们的许多基本思想可以应用于一般的模拟，其有效的实例化的细节是非常依赖于域。 在这个项目中的大部分研究将集中在利用这个想法的网络模拟的背景下，特定的，重要的网络协议和体系结构类。 我们考虑两种具体的方法，一种是基于使用可更新的模拟和其他基于模拟克隆。2. 我们的第二个研究领域使用作为一个出发点，假定能够进行大规模的网络模拟实验。我们要问的主要问题是，为了得出正确的“互联网规模”结论，模拟实验应该有多大？无可否认，这是一个很难回答的问题。然而，我们认为，大规模网络模拟的最新进展使最终开始解决这个问题成为可能。 我们现在能够考虑网络模拟的非平凡缩放对结果的影响，这项工作的目标是开发和分析一个系统的，动机良好的方法来回答“多大是足够大？“问题。 我们提出了一个稻草人的方法，这将代表我们的调查的起点。 我们还提供了实验证据，证明规模如何影响模拟结果。

The study of computer networks, while a relatively young science, is no different from any scientific inquiry and as such needs to be built on top of a theory-validated-by-experiment foundation. In this award we focus on the use of computer-based simulation which provides the greatest flexibility in creating a general experimentation environment. Simulation offers several important challenges, however. First is the fact that the Internet is an ever changing, highly heterogeneous environment that is typically very difficult to model. Second is the question of how to faithfully reflect the large scale of the Internet in a computer-based simulation. We are primarily interested in addressing this latter challenge in this research. Our interest in large-scale network simulation is motivated by the fact that we view network simulation as an important tool to understand the true effect of a new protocol, mechanism, network service, or application when widely deployed on a large network such as the Internet. It is clearly problematic to simply extend conclusions derived from small simulations and make inferences regarding effect and behavior when extended to a large scale.While simulation of networks at the scale of the Internet remains infeasible today, there has been considerable progress made in the last few years in increasing the scale capability of network simulations. Our work uses this improved scaling capability as a starting point. This award represents an effort to go beyond the question of how to perform a large scale simulation run and address the question of how to perform a large-scale simulation experiment. A simulation experiment typically consists of multiple related runs and is also defined by a specific validation and/or evaluation objective (e.g., what will happen if an ISP enables a certain queue management algorithm in all its routers). We note that our work focuses primarily on packet-level discrete-event simulation, as opposed to other approaches that allow scaling through aggregation and approximation. Our goal is to understand the limits of faithful packet-level discrete event simulation as a vehicle for experimentation and validation.With the goal of investigating the question of how to perform large-scale simulation experiments we focus on two principal areas of research: 1. We will develop and analyze techniques that allow for the efficient execution of multiple network simulation runs. A key observation is that the multiple runs that make up an experiment are often related. Exploiting this fact, we will develop techniques to allow computations from one run to be reused in other runs, thereby reducing the amount of time to complete a set of runs. Our preliminary work demonstrates the feasibility of this approach. We note that while many of our basic ideas can be applied to simulations in general, the specifics of their efficient instantiation is very much domain dependent. Much of the research in this project will focus on exploiting this idea in the context of network simulations for specific, important classes of network protocols and architectures. We consider two specific approaches, one based on the use of updateable simulations and the other based on simulation cloning. 2. Our second area of research uses as a starting point a presumed ability to perform large-scale network simulation experiments. The main question we ask is how large should a simulation experiment be in order for one to reach correct ``Internet-scale" conclusions? This is admittedly a very hard question to answer. We feel, however, that recent advances in large-scale network simulations have made it possible to finally begin to address this question. We are now capable of considering the effect of non-trivial scaling of a network simulation on the results derived from it. The goal of this work is to develop and analyze a systematic, well-motivated approach for answering the "how large is large-enough?" question. We present a strawman approach which will represent the starting point of our investigation. We also provide experimental evidence demonstrating how scale can affect simulation results.