On the Vulnerability of Mega-Constellation Networks Under Geographical Failure

Assessing the vulnerability of mega-constellation networks (MCNs) to large-scale failure is challenging, due to the time-varying three-dimensional constellation. In this paper, we propose a geometrical method to assess the vulnerability of the MCNs under large-scale geographical failure based on the standard +Gridinter-satellite connectivity pattern, using hop count as the metric. We first equivalently map the original constellation to a two-dimensional flat torus, offering a simplified and time-invariant representation of the geographical failure. The failure’s properties are then revealed on the torus to identify the blockage on the inter-satellite paths that might increase the hop count between end users. Under the blockage, a closed-form hop count expression is then obtained by deriving the explicit expressions of the optimal detours in the scaling limit. Finally, we propose a low-complexity hop count estimation algorithm that achieves a maximum relative error of 1.5% compared with the network simulation while being$10^{5}$times faster. Evaluations using traffic sourced from the 100 most populous cities show that the geographical failure covering the latitude corresponding to the MCNs’ inclination has the greatest impact on the hop count, whereas the MCNs are generally robust even under extreme scenarios.