## 3 Reference Scenario and Problem Statement
All of the solutions proposed in the literature aim to minimize the energy consumed in the satellite for on-board processing, but this choice may lead to a waste of the photovoltaic energy produced. Indeed, once the batteries are fully charged, the excess energy produced by the photovoltaic panels is dissipated or otherwise not used. In contrast, the GS operates on an on-demand energy usage model, which depends on the number of tasks being processed. For this reason, the objective of the paper is to propose a resource allocation strategy that exploits all of the energy produced in the satellite. The resulting advantage is the possibility of saving energy in the ground station due to the reduction in the number of tasks processed. We highlight the advantages in the example reported in Figure 2. In particular, in both cases (a) and (b), we have a satellite first acquiring an image of a predefined region, then moving on its orbit until reaching a position B where the satellite is sunlit and the battery can be charged by means of solar panels, and finally reaching a position C where the acquired information can be downlinked to the ground. In case (a), no processing occurs in orbit. In particular, the satellite acquires the image, and when it reaches position B it has half its battery charge. However, from B to C, the satellite is sunlit, and during the movement from B to C, the battery gets fully charged. Finally, when the satellite reaches position C, the acquired image is downlinked and processed by the ground station. Instead, in case (b), the satellite processes the acquired image when it reaches position B. For this reason, the on-board battery has a smaller charge with respect to position B in the former case. However, in the path from B to C, the satellite receives enough solar radiation to charge the battery even though the initial energy is lower. Thus, battery is again fully charged when the satellite sends the already processed image to the GS in position C, and at the same time we saved energy on the ground. From this example, it follows that, even though on-board energy is a limited and valuable resource, it is renewed whenever the satellite is sunlit, and for this reason it is not important to minimize its usage, but to optimize it in such a way that by leveraging, when possible, the energy available on satellites, we can reduce the consumption on the ground. Obviously, the usage of extra energy available on board the satellites may lead to an increased number of battery charge-discharge cycles, and this may reduce the operative life of each satellite. However, it is difficult to quantify the cost of this operative life reduction and to compare it to the savings resulting from a smaller use of on-ground energy, since it is strictly related to the specific mission. Furthermore, a more complex problem which takes into account this cost can be also proposed, but it is beyond the scope of this work, since we want to first study the energy savings which can be obtained by leveraging OEC and satellite networks, and to provide some insight on how processing capacity available on board the satellites has to be chosen to maximize the energy savings on the ground. Finally, in terms of operating cost, it has already been discussed in the literature that, following appropriate resource allocation and processing placement strategies, the total operating cost when data are processed on board is smaller than when processing happens on ground, since a reduced amount of information has to be transferred [29].