A multi-layer temporal network model of the space environment

TLDR: A representation of the space environment as a dynamic multilayer network, where space objects are nodes and their relationships are captured through dynamic links; each layer represents a different type of interaction.

Abstract: With the advent of the New Space era and the increase in the population of resident objects in Earth orbit, there is a compelling need to adopt new tools to study the complexity of the space environment. In particular, there is a need to consider the different layers of functionalities and services in an integrated and consistent framework that allows a global analysis of the evolution of the space environment. In the past two decades, there has been intense research to describe and model physical, engineering, information, social and biological systems using network theory. Most recently, multilayer networks, or networks of networks, have demonstrated a higher capability of describing failures, relationships, connectivity, and patterns, with respect to their single-layer counterpart. This paper presents a representation of the space environment as a dynamic multilayer network, where space objects are nodes and their relationships are captured through dynamic links; each layer represents a different type of interaction. In this paper, in particular, we consider two layers: the physical and the information layer. The former models the collision between pairs of objects and how disruptions tend to propagate in the network, while the latter models the exchange of information among satellites via telecommunication. Links are probabilistic in that they model the probability of an interaction between two nodes. Moreover, the spreading dynamics of disruptions among nodes is mathematically described with a susceptible-infectious-susceptible epidemiological model. By using a bottom-up approach, where we stochastically simulate the spreading of a disruptive event in the network, we show how it is possible to investigate different spreading scenarios and analyze the network weak links and nodes, which can then be targeted for improving the space environment resilience.