## 1 Introduction  
One of the most important limitations Earth Observation (EO) satellites have to face is related to the transmission of a huge amount of information to the ground in a limited amount of time in the moments during which there is a visible Ground Station (GS). In fact, nowadays, satellites typically acquire images when flying over regions of interest, store them into on-board memories, and then downlink all the gathered images to a GS when in an appropriate visibility region. To accomplish the delivery of this high amount of data (e.g., notice that a Sentinel-2 satellite produces 160 Mb of data for each second of flight over a region of interest [1]), it would be then necessary to increase either the downlink data rate or the number of GSs, both being unscalable with the increase of collected data. In particular, the data rate for transmissions from a satellite is constrained by the power available on board, which is in turn constrained by the dimensions and masses of solar panels and batteries. However, a third way to face these limitations can be given by the Orbital Edge Computing (OEC) [2], which allows the leveraging of satellites in EO constellations to process data on board. This approach is being also studied in the context of Mega-LEO constellations [3; 4] in Non-Terrestrial Networks (NTNs) [5] or Space-Air-Ground Integrated Networks (SAGINs), which are being designed to support applications dedicated to 5G [6] and 6G [7]. The beneficial impact of such a solution in the EO context is surely related to the fact that not all data transmitted to the ground are actually useful to the application. For example, in a fire detection application [8], we are only interested in communicating the presence of a fire in a forest, without having to make the full image available on the ground to then be elaborated. Thus, an on-board selection of the information to be transmitted thanks to on-board data processing could better exploit the limited bandwidth, since only useful information is transmitted [9; 10; 11; 12], and also contributes to lowering the time needed to deliver information to the ground station, in particular when Inter-Satellite Links (ISLs) are available [13; 14; 15]. In a complementary manner, an efficient use of on-board processing resources could also enable the transmission of a larger amount of data to the ground under the same bandwidth constraints. In order to obtain these benefits, several strategies have been identified to decide where data will be processed (satellite or GS) [16; 17; 18]. However, these solutions assume that processing can only be carried out by the satellite acquiring the information, while further advantages can be obtained by considering that idle satellites can be leveraged to elaborate information acquired by another satellite, in case this does not have enough resources to deal with the processing. A further important benefit of OEC can be found in the savings we can obtain in energy consumption on GSs when data are processed in orbit. In particular, it can be noticed that, once a satellite is in orbit, energy generation always happens (e.g., solar panels always generate power when exposed to solar radiation), and the amount of generated energy is only dependent on the exposure of solar panels to the sun. In other words, we allocate in advance an amount of energy by providing for a certain worst-case energy budget, and the satellite always makes it available, regardless of its actual use, and since it is generally generated through solar panels, it is completely sustainable energy. Satellite-based ground stations play a crucial role in the communication and navigation systems that we rely on daily. These stations receive and transmit signals from satellites orbiting the Earth, enabling a wide range of applications, from weather forecasting and disaster management to global positioning and television broadcasting. As demand for satellite-based services continues to grow, so does the need for GSs.