DOMINOS: Dissecting and Modeling Interdependencies in Communication Networks
Our society is becoming increasingly reliant on the Internet and cellular networks for both critical and leisure services. At the same time, these networks are becoming increasingly complex. Network operators depend on each other to extend their reach and to increase their capacity. Furthermore, the interaction between these networks and their surrounding eco-system, encompassing everything from the physical infrastructure they run on to the policies regulating their operations, are far from being understood. Understanding these interdependencies is crucial for avoiding large-scale failures. Regulators, network operators, and customers are all interested in understanding these dependencies. This understanding will help regulators in devising better policies to ensure the stability of these critical infrastructures. Operators will leverage such understanding to improve their services, and customers will be able to make informed decisions when buying communication services.
Dominos aims to investigate interdependencies in complex systems that are organized as a network of networks with emphasis on communication networks. We will follow an experimental approach by measuring real systems. Then develop computational models that adequately resemble real networks and use to answer intricate what-if questions. We believe that this work can help both expanding our understanding of interdependencies in communication networks as well as serve as an input to other disciplines that study complex interdependent networks.
We would like to develop a framework for empirically quantifying interdependencies in communication systems that are organized as networks of networks. Such framework will help different stakeholders including regulators, operators, and end users gaining insights into the overall reliability of the systems they manage, own, operate and use. We would like also to develop analysis tools that can be reused by research that studies networks of networks in different contexts. For example, biological networks of networks and financial and trade networks. Thus, enabling future opportunities for interdisciplinary collaborations.
The Research Council of Norway