NeTS: Small: Meta-Modelling for Complex Engineered Networks

NeTS：小型：复杂工程网络的元建模

基本信息

批准号：
1421058
负责人：
Violet Syrotiuk
金额：
$ 50万
依托单位：
Arizona State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2014
资助国家：
美国
起止时间：
2014-10-01 至 2020-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1421058&HistoricalAwards=false
关键词：
NeTS Small Meta Modelling Complex

项目摘要

Complex engineered networks are pervasive in everyday life. A few examples include the internet, power grid, and transportation networks. The complexity arises not just from the size of the network, but also its structure, operation, evolution over time, and the fact that people are involved in its design and operation. Understanding complex engineered networks is challenging; their size and emergent properties means that traditional techniques of design, analysis, and modelling are poorly suited to adequately characterizing their behaviour and fundamental properties. This project develops a new tool for rigorous design, analysis, and modelling in the context of wireless networks. The goal is to improve understanding of the factors and interactions that impact performance. Experimentation in simulation and testbeds, using the NSF Global Environment for Network Innovations (GENI) network, is ongoing.Locating arrays (LAs) are formulated to focus on identification of factor interactions rather than measurement. Consequently, designs using LAs grow logarithmically in the number of experimental factors. This makes practical an order of magnitude more factors in experimentation. Hence, LAs have the potential to transform experimentation in huge factor spaces such as those found in complex engineered networks. An iterative approach, similar to that used in compressive sensing, is applied in model development; this also addresses a grand challenge in wireless networks for new data-driven mathematical models. Assessing the validity and robustness of the models developed is essential to understanding their quality and usefulness for optimization, management, and control of the network. Overall, this project contributes to understanding of complex engineered networks that shape modern society.

复杂的工程网络在日常生活中普遍存在。一些例子包括互联网、电网和交通网络。复杂性不仅源于网络的规模，还源于其结构、操作、随时间的演变，以及人们参与其设计和操作的事实。理解复杂的工程网络具有挑战性；它们的规模和涌现的特性意味着传统的设计、分析和建模技术不太适合充分描述它们的行为和基本特性。该项目开发了一种新工具，用于在无线网络环境中进行严格的设计、分析和建模。目标是提高对影响绩效的因素和相互作用的理解。使用 NSF 全球网络创新环境 (GENI) 网络进行的模拟和测试台实验正在进行中。定位阵列 (LA) 的设计重点是识别因素相互作用而不是测量。因此，使用 LA 的设计实验因子的数量呈对数增长。这使得实验中的实际因素增加了一个数量级。因此，LA 有潜力改变巨大因素空间中的实验，例如复杂工程网络中的实验。与压缩传感中使用的迭代方法类似，模型开发中采用了迭代方法；这也解决了无线网络中新的数据驱动数学模型面临的巨大挑战。评估所开发模型的有效性和鲁棒性对于了解其质量和对网络优化、管理和控制的有用性至关重要。总体而言，该项目有助于理解塑造现代社会的复杂工程网络。