## 8 Conclusions  
In this paper, we evaluated how the combined application of both satellite networks thanks to Inter-Satellite Links and edge computing capabilities on board satellites can be fruitfully leveraged by EO satellite constellations to save energy on GS by elaborating images directly on board of satellites instead of on the ground. This allows us to better leverage an amount of unused energy which is preallocated on board satellites, instead of requiring extra energy on the ground. We formalized and solved an optimization problem to find the optimal energy savings, which however was determined to be NP hard. For this reason, we also proposed the Ground Station Energy-Saving Heuristic (GSESH) Algorithm to be applied to a real orbital scenario. We showed that even with a small amount of energy available on board the satellites, it is possible to obtain substantial energy savings on GSs.  
Figure 14: Ground station energy saving obtained by applying the proposed GSESH algorithm by varying the number \(\alpha\) of services processable on a satellite in a time cycle and the number of cores available on board of satellites, with \(\
abla=1\%\) of Sentinel-2 energy available for OEC.  
Figure 13: Ground station energy saving obtained by applying the proposed GSESH algorithm by varying the number \(\alpha\) of services processable on a satellite in a time cycle and the \(\
abla\) percentage of Sentinel-2 energy available for OEC operations.  
In particular, we have verified that the GSESH algorithm allows for energy savings in the ground station up to 40% higher than those achieved with the benchmark solution in a real scenario. However, although intuitively one might assume that the higher the computational capacity on board the satellites, the higher the ground station energy saving (since more data are processed in orbit), we showed that the limitation on the energy available on board the satellites is such that there is a CPU clock frequency value for which the maximum ground station energy saving is achieved, above which this saving starts decreasing because even though there is a higher computational capacity, the energy to be used to process every single task also increases, and the small amount of energy available on board is such that there is not enough energy to leverage the full available computational capacity. Future work will explore a more realistic modeling of solar energy dynamics on board satellites, distinguishing between direct solar input and battery storage, as well as accounting for eclipse periods. Additionally, future extensions could relax the fixed time-slot assumption by allowing for processing and transmission operations to span multiple or variable-length time slots, thus improving scheduling flexibility and resource utilization.  
Conceptualization, F.G.L. and V.E.; Methodology, M.P.; Software, T.F.; Formal analysis, M.P.; Investigation, F.V.; Writing--original draft, F.V.; Writing--review & editing, F.G.L.; Visualization, T.F.; Supervision, V.E. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.