Abstract Large-scale disasters can severely disrupt Information Technology (IT) infrastructure, e.g., Data Centers. Earthquakes, hurricanes, tsunamis, and other natural catastrophes may lead to such a scenario. Man-made threats, e.g., a High-Altitude Electromagnetic Pulse (HEMP), can also provoke such an aftermath. In the HEMP case, however, the aftermath might include damage even to non-terrestrial IT infrastructure, such as satellites. After any disaster, it is important that critical data located in the affected region be evacuated to secure locations where it can be useful for emergency operations, mission-critical activities, rescue and relief efforts, and society and businesses in general. To minimize the time it takes to perform this evacuation, we must use all available resources as efficiently as possible. This includes using the remaining satellites to connect the affected regions of the network to the unaffected ones. Utilizing the Software-Defined Network (SDN) paradigm applied to satellite networks, we propose an algorithm that can be executed by the SDN controller. This algorithm generates an evacuation plan for data located in possibly-isolated terrestrial systems, such as Data Centers, through the satellite network, towards final destinations in the main network. The evacuation plan is a transmission schedule that maximizes the amount of evacuated data. Considering the current industrial interest in mega satellite constellations, we compare how two constellations of 66 and 720 satellites perform in terms of amount of data evacuated. Our results show how the evacuation is affected by different satellite constellation configurations (i.e., buffers, inter-satellite link capacities, etc.). Since our approach allows for Traffic Engineering (TE) to be performed, we also demonstrate how it enables fair resource utilization among different affected infrastructures during data evacuation. Our illustrative examples also compare our method to an approach designed for Delay-Tolerant-Vehicle networks and show how our solution can evacuate up to 60% more data after a disaster.
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