By endowing satellites in Earth Observation (EO) constellations with Orbital Edge Computing (OEC) capability, i.e, with the ability of processing acquired images directly on-board, it is surely possible to use bandwidth more effectively, since only the actual useful information extracted from the image is transferred on ground. However, OEC can be fruitfully leveraged also to minimize the energy consumption on ground stations due to image processing. In fact, in EO satellites energy is allocated in advance by endowing them with appropriate solar panels and batteries, and this amount of energy is always generated, even when it is not necessary. On the contrary, energy on ground station is closely related to its demand. For this reason, we propose and investigate a strategy to allocate processing and bandwidth resources in OEC-endowed EO satellite network to minimize energy consumption on ground stations due to on-ground processing. By taking into account the energy budget on Sentine1-2, having a 26% of available energy being unused, we show how with our approach it is possible to obtain a substantial reduction in energy consumption on ground stations even by using the 1% of the total energy budget when appropriate computational capacity is available on board, while this consumption can even drop to zero by increasing the energy dedicated to OEC operations to the 15% of the energy budget.

A resource allocation strategy in earth observation orbital edge computing-enabled satellite networks to minimize ground station energy consumption / Valente, F.; Lavacca, F. G.; Eramo, V.. - (2023), pp. 1-6. (Intervento presentato al convegno 36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023 tenutosi a Miami (Florida)) [10.1109/NOMS56928.2023.10154220].

A resource allocation strategy in earth observation orbital edge computing-enabled satellite networks to minimize ground station energy consumption

Valente F.
;
Lavacca F. G.;Eramo V.
2023

Abstract

By endowing satellites in Earth Observation (EO) constellations with Orbital Edge Computing (OEC) capability, i.e, with the ability of processing acquired images directly on-board, it is surely possible to use bandwidth more effectively, since only the actual useful information extracted from the image is transferred on ground. However, OEC can be fruitfully leveraged also to minimize the energy consumption on ground stations due to image processing. In fact, in EO satellites energy is allocated in advance by endowing them with appropriate solar panels and batteries, and this amount of energy is always generated, even when it is not necessary. On the contrary, energy on ground station is closely related to its demand. For this reason, we propose and investigate a strategy to allocate processing and bandwidth resources in OEC-endowed EO satellite network to minimize energy consumption on ground stations due to on-ground processing. By taking into account the energy budget on Sentine1-2, having a 26% of available energy being unused, we show how with our approach it is possible to obtain a substantial reduction in energy consumption on ground stations even by using the 1% of the total energy budget when appropriate computational capacity is available on board, while this consumption can even drop to zero by increasing the energy dedicated to OEC operations to the 15% of the energy budget.
2023
36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023
earth observation; energy saving; LEO satellite networks; orbital edge computing
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A resource allocation strategy in earth observation orbital edge computing-enabled satellite networks to minimize ground station energy consumption / Valente, F.; Lavacca, F. G.; Eramo, V.. - (2023), pp. 1-6. (Intervento presentato al convegno 36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023 tenutosi a Miami (Florida)) [10.1109/NOMS56928.2023.10154220].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1706657
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