NeTS: Small: Meta-Modelling for Complex Engineered Networks

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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.