The next step in Earth Observation (EO) constellations will be leveraging Inter-Satellite Links (ISLs) to form a network where information generated by the EO application can be transmitted, in such a way that, by endowing spacecrafts with processing capacity, observation data may be processed directly in orbit by any satellite of the constellation. However, since bandwidth and on-board processing capacity are valuable resources, strategies to appropriately routing the information and deciding on which node it has to be processed shall be defined. In this work, we formalize and solve an optimal bandwidth and computing resource allocation problem in Low Earth Orbit (LEO) satellite constellation for EO applications. In order to deal with the complexity of the proposed optimization problem, we also present two heuristics requiring different computational effort. In the proposed problem formalization, processing can happen on any node of the network (i.e., either on the data source satellite, on any other satellite of the constellation or on ground station). After having validated the proposed heuristics by comparing their results to the optimization problem ones, we apply them to a real orbital scenario, showing their ability to reduce both total cost and data delivery delay to ground with respect to state-of-the-art solutions.
Optimal bandwidth and computing resource allocation in low earth orbit satellite constellation for earth observation applications
Lavacca F. G.
2023-01-01
Abstract
The next step in Earth Observation (EO) constellations will be leveraging Inter-Satellite Links (ISLs) to form a network where information generated by the EO application can be transmitted, in such a way that, by endowing spacecrafts with processing capacity, observation data may be processed directly in orbit by any satellite of the constellation. However, since bandwidth and on-board processing capacity are valuable resources, strategies to appropriately routing the information and deciding on which node it has to be processed shall be defined. In this work, we formalize and solve an optimal bandwidth and computing resource allocation problem in Low Earth Orbit (LEO) satellite constellation for EO applications. In order to deal with the complexity of the proposed optimization problem, we also present two heuristics requiring different computational effort. In the proposed problem formalization, processing can happen on any node of the network (i.e., either on the data source satellite, on any other satellite of the constellation or on ground station). After having validated the proposed heuristics by comparing their results to the optimization problem ones, we apply them to a real orbital scenario, showing their ability to reduce both total cost and data delivery delay to ground with respect to state-of-the-art solutions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.