MODELING, ANALYSIS, AND OPTIMIZATION OF ROBUSTNESS IN INTERDEPENDENT NETWORKS
Abstract
It is increasingly the case that most complex networks do not live in isolation, and that they exhibit significant inter-dependencies with each other. It has been shown that interdependence and coupling among networks lead to dramatic changes in network dynamics, with many studies focusing on cascading failure and robustness. However, most existing works use percolation-based models where only the largest component of each network remains functional throughout the cascade. Although suitable for communication networks, this assumption fails to capture the dependencies in systems carrying a flow (e.g., power systems, transportation networks, supply-chain networks, etc.), where cascading failures are often triggered by redistribution of flows leading to overloading of network components. Also, very few works consider engineering aspects of interdependent networks and very little is known as to how such systems can be designed to have maximum robustness under certain design constraints. The current literature also lacks realistic and general dependency models that capture fundamental differences between physical and cyber networks and enable studying robustness of systems that integrate networks of different nature. This project will advance the state-of-the-art in modeling complex interdependent networks, and in analysis and optimization of their robustness against random failures and targeted attacks. We will develop a general interdependent system model that will help understand how failures would propagate and escalate in an interdependent system. We will concentrate on two specific frameworks- i) an interdependent system model that integrate physical and cyber networks with the constituent networks following fundamentally different intra-dependency rules; and ii) an interdependent system model where two or more networks carrying substitutable commodities are coupled together. These frameworks are motivated by a wide range of applications relevant to DoD mission including cyber-physical systems, critical infrastructures, supply-chain systems, transportation systems, etc.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502210233
Entities
People
- Osman Yagan
Organizations
- Air Force Office of Scientific Research
- Carnegie Mellon University
- United States Air Force