NeTS: Small: Tools for Large-Scale Network Testbed Experimentation

在过去的十年里，美国无线互联网连接设备的使用几乎翻了一番，用户推动了新的社会有用的应用程序。尽管预计这些工程化网络在多种情况下的行为是可预测的，但它们具有复杂的行为，表现出使用传统技术不易研究的特征。实验是提高我们理解能力的一种方式。在网络、设备和环境的众多参数中，实验中必要的第一步是筛选那些对性能有显著影响的参数进行后续研究。该项目通过开发与测试台集成的工具来应对无线网络中的重大挑战，从而为国家利益做出贡献。在这种情况下，筛选的最低要求被捕获在定位阵列(LA)中。LAS在参数个数上呈对数增长，使实验中实际考虑的参数多一个数量级。LA的结构和恢复重要参数的分析以及影响测量性能的双向相互作用是紧密耦合的。虽然筛查的基本要求是已知的，但对恢复的基本要求还没有很好地理解。如果需要平衡，则应用RAO界限，并且数组大小必须在参数和双向交互的数目中以多项式增长。方法包括使恢复算法在LA中缺乏平衡的情况下工作，或者使LA更适合于恢复。实际的网络应用激发了LA上的新结构，进而影响了恢复。该项目的目标是生产与试验台集成的工具(1)为大规模试验台试验生成和验证筛选设计，以及(2)用于随后的分析。该项目在两个主要领域推进了研究：(1)了解对恢复的要求，以及阵列结构和恢复的权衡，从而帮助在新型LAS和传统筛选设计之间架起一座桥梁。(2)有效使用筛选设计需要部署支持这些设计的工具。用于构建、验证和分析LAS的新型开源工具将被开发并集成到无线网络试验台中。这些工具将在社区范围的储存库中提供，配备了文档和培训材料，包括将它们与各种测试台集成的步骤。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Over the last decade, the use of wireless Internet-connected devices has nearly doubled in the U.S., with users fueling new socially useful applications. Despite being expected to behave predictably under a wide set of circumstances, these engineered networks have complex behaviors, exhibiting characteristics not easily studied using traditional techniques. Experimentation is one way to improve our understanding. Among the many parameters of the network, the devices, and the environment, a necessary first step in experimentation is screening to select those that significantly impact performance for follow-on study. This project contributes to the national interest by developing tools integrated with test-beds to address grand challenges in wireless networks.The minimum requirements for screening in this setting are captured in a locating array (LA). LAs exhibit logarithmic growth in the number of parameters, making practical the consideration of an order of magnitude more parameters in experimentation. The structure of the LA and the analysis to recover the significant parameters and two-way interactions impacting the measured performance are tightly coupled. While the basic requirements of screening are known, the basic requirements of recovery are not well understood. If balance is required, then the Rao bound applies, and the array size must grow polynomially in the number of parameters and two-way interactions. Approaches include either making the recovery algorithm work with the lack of balance in the LA, or making the LA more suitable for recovery. Practical networking applications motivate new structure on the LA that in turn impacts recovery. The goals of this project are to produce tools integrated with testbeds (1) to generate and validate screening designs for large-scale test-bed experimentation, and (2) for their subsequent analysis. This project advances research in two primary areas: (1) Understanding the requirements for recovery, and the trade-offs in array structure and recovery, thus helping to build a bridge between novel LAs and traditional screening designs. (2) The effective use of screening designs requires the deployment of tools to support them. Novel open source tools to construct, verify, and analyze LAs will be developed and integrated in a wireless network test-bed. The tools will be made available in a community wide repository, equipped with documentation and training materials, including steps to integrate them with a variety of test-beds.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.