# Space Edge Computing for Satellite Systems: Definition and Key Enabling Technologies

D. Chenet, J. Lorandel, C. Moy, S. Ramirez-Gallego, R. Regada Alvarez

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D. Chenet, J. Lorandel, C. Moy, S. Ramirez-Gallego, R. Regada Alvarez. Space Edge Computing for Satellite Systems: Definition and Key Enabling Technologies. 30th European Conference on Parallel and Distributed Processing-Euro-Par, Aug 2024, Madrid, Spain. 10.1007/978-3-031-90203-1_48. hal-05370953

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# Space Edge Computing for Satellite Systems: Definition and Key Enabling Technologies

D. Chenet¹,²✉, J. Lorandel², C. Moy², S. Ramirez-Gallego¹, and R. Regada Alvarez¹

¹ Thales Alenia Space, C\Einstein 7, 28760 Cannes, Spain
{d.chenet,s.ramirez-gallego,r.alvarez}@thalesaleniaspace.com

² Univ Rennes, CNRS, IETR-UMR 6164, 35000 Rennes, France
{d.chenet,j.lorandel,c.moy}@univ-rennes.fr

**Abstract.** This paper addresses some of the key enabling technologies for emerging space edge computing systems. A specific definition of space edge computing for satellite systems orbiting the earth is given, showing how the computing power in future satellite systems can be improved, in particular through innovative on-board data handling architectures and distributed processing between satellites.

**Keywords:** On-Board Data Handling · Components Off The Shelf · Artificial Intelligence · Edge Computer · Distributed Satellite Systems · Inter-Satellite Links

## 1 Introduction

Due to the high cost of launch to orbit, satellite systems have always been designed as monolithic platforms, embedding all necessary elements for the mission i.e. sensor, navigation, telecommunication, etc. In observation missions, data produced by embedded sensors are usually stored in the satellite, then forwarded to the ground to be processed. However, as sensors grow more complex and produce an increasing amount of data, it becomes interesting to process data on-board to tap into the full power of cutting-edge sensors. Meanwhile, in the telecommunication domain, companies are looking to provide computing power as a service to ground users, airborne systems and other systems in orbit. Enabling satellite systems to process user data in orbit is thought to improve the quality of service by providing a higher availability and lower latency. Finally, with the recent development of reusable launchers, the cost of an orbital launch has been drastically reduced, making way for multi-satellite missions.

In this paper, our contribution is to bring together the domains of on-board data handling (OBDH) computer architecture and distributed satellite systems, highlighting key enabling technologies for the development of space edge computing. We believe that the proposed transversal vision would help many actors of the domain identifying the potential of this technology in a common way.
## 2 State of the Art

Space Edge Computing (SEC) has become a topic of importance within the last few years as several private and scientific missions were launched to demonstrate new technologies. For instance, one of the goals of the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME), as part of the European Space Agency's (ESA) Copernicus mission program, is to demonstrate embedded AI as a way to process large quantities of data in orbit for Earth Observation satellites [10]. As part of the Japan Aerospace Exploration Agency's program, GPU Components Off-The-Shelf (COTS) were used in the GEMINI [2] payload to study the behaviour of these devices in space. Private companies are also actively involved in the development of SEC. In particular, the SpaceBorne Computer development program, led by Hewlett Packard Enterprise, sought to qualify the reliability of their supercomputer products in the space environment on-board the ISS. Lastly, in the telecommunication domain, the Starlink mega-constellation demonstrated the importance of inter-satellite links (ISLs) to enable data sharing between satellites. An analysis of ISL paths for low earth orbit (LEO) mega-constellation networks relying on Starlink's constellation architecture is presented in [1].

In parallel, many research works contribute to enable SEC, with specific fields of interest. In particular, a review of machine learning techniques for earth observation operations was presented in [5]. Another review details the challenges issues regarding the implementation of artificial intelligence in space systems at hardware level [3]. In [6], architectures and synchronisation techniques for distributed satellite systems are addressed. Other works present innovative inter-satellite link technologies based on radio-frequency and optical links.

While SEC is an increasingly cited topic, its definition is a lingering problem as it can be different from one study to another depending on the context: "Edge Computing in space", "Orbital Edge Computing", "Satellite Edge Computing". In the next section, a specific definition of SEC is proposed for the scope of this paper.

## 3 A Proposed Definition of Space Edge Computing for Earth's Orbit Applications

A generic definition of Edge Computing is given by [7]: Edge Computing "refers to the enabling technologies that allow computation to be performed at the network edge so that computing happens near data sources". While this definition can be applied to satellite systems, it does not take into account the particularities of their interconnections. In fact, most of the time, data are not processed in orbit within the satellite that receives them, they are forwarded to a base station through an earth link and then to a data center through terrestrial networks. In the scope of this work, a more specific definition could be refined as "Space Edge Computing refers to the technologies that allow to distribute and perform computation in orbit, close to the data sources". Figure 1 shows the possible
data sources for a system in orbit of the earth relative to the position of the receiving satellite, that could come either from ground, airborne or lower orbit systems (a), internal sensors (b), external system on the same orbit (c) or higher orbit and space (d). As illustrated on Fig. 2, SEC is enabled by both a flexible OBDH architecture relying on various processing elements and interconnections allowing a flow of data between the different system levels. An Edge Computer is an OBDH module dedicated processing data coming from one or multiple of the data sources previously cited. We call an Edge Node a satellite specifically dedicated to data processing in orbit.

<figure><img src="image_2.png" /><figcaption>Fig. 1. Data Sources for a System in Orbit of the Earth</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>Fig. 2. OBDH architecture and interconnections in SEC systems</figcaption></figure>
# 4 On-Board Data Processing

To satisfy the reliability requirements for space systems, hardware processing elements have to be hardened against radiations (rad-hard). Physical hardening is performed by the manufacturer by using specific design techniques. However, physical hardening has an impact on the specifications and performances of these devices which drives rad-hard components to have lower specifications than state-of-the-art COTS. Considering this context, the space industry shows a growing interest in the integration of COTS in satellite systems as they provide better specifications than rad-hard components.

Other technologies like artificial intelligence (AI) are investigated as solutions to bring more computing power into satellite systems. Typically used for image processing, AI allows to process large amounts of data in orbit. A recurring problem in earth observation missions is the presence of clouds on images. For missions observing the ground, images containing a too high proportion of clouds are not exploitable. AI and object recognition can help to sort out cloudy images from valuable images, hence saving storage space in the satellite and saving power on data transmission to the ground. AI is also used for data compression, thus reducing the amount of data to be transferred to the ground and saving power on telecommunications.

However, integrating AI into satellites is also a challenge as the relying hardware components currently used on the ground are not yet ready to be used in space. As example, The GPU for Space (GPU4S) initiative led by ESA aims at identifying if GPU components could be used in satellite systems. Other components like video processing units (VPUs) are also seeing a lot of attention as illustrated in the PHI-SAT mission.

OBDH computers are usually designed to meet the needs of a specific mission, providing very little reprogrammability. The space industry is actively developing generic OBDH computers called edge computers that can be easily reprogrammed in orbit to run applications of various nature. Edge Computers allow to provide computing power in orbit as a service, in a similar fashion as cloud servers on ground. Companies like Thales Alenia Space (TAS) are actively involved in the development of edge computing platforms. In May 2024, TAS in collaboration with Microsoft Azure launched their Imagin-E payload to the ISS to investigate the integration of high-performance edge computers in satellite platforms.

# 5 Distributed Processing

To collaborate, satellites need to be able to synchronize and share data. In this context, Inter-satellite links (ISL) are a promising technology. In the past, ISLs have only seen a commercial use in telecommunication constellations. One of the earliest service relying on ISLs is the Iridium LEO constellation composed of 66 satellites using RF-ISLs providing a throughput of 25-Mbit/s between satellites [4]. Today, ISLs can be based optical links which convey data between satellites through laser terminals. Multiple mega-constellation projects integrate optical
ISLs, most notably Starlink and OneWeb. Over long distances, optical ISLs provide higher data rate than RF-ISLs because laser beams provide less scatter than RF lobes. The data rate of optic ISLs can go up to several Gbit/s. Both RF-ISLs and optical ISLs are still facing many challenges such as the reduction of mechanical parts required to steer the beams as well as the power consumption, the size and the cluttering. As RF-ISLs seem to be outperformed by optical ISLs in terms of power consumption and throughput for long distances, RF-ISLs are presented to find a use in satellite swarms.

Using ISLs, satellites within a constellation can perform load balancing [8]. While orbiting the earth, a satellite may enter a no-service zone and a standby state, effectively not using its computing capacities. By performing load balancing, an operating satellite is able to transfer a part of its tasks to a neighboring satellite with more available resources. By this way, the power consumption of data handling can be smoothed out over multiple satellites, using in priority the satellites that dispose of more power resources. Load balancing also provides additional advantages like resilience and redundancy in case of failure on a data processing component.

Through load balancing comes the idea of creating satellites which are only meant to compute tasks coming from other satellites, in Edge Computing they are called edge nodes. In [9] an Edge Computing constellation architecture called iSat was proposed, providing computing power as a service not only to other satellite systems but also to terrestrial and airborne users. Edge Computing constellations are thought to be an evolution of the telecommunication mega-constellations by bringing together both connectivity and computing power in the same satellite platforms. This way, tasks can be processed close to the data sources without having to forward the data to a distant base station and data center.

However the computing capabilities that can be embedded into conventional satellite platforms remain low in performance compared to terrestrial data centers. As part of a research program enabled by the European Union, Thales Alenia Space launched the “Advanced Space Cloud for European Net zero emission and Data sovereignty” (ASCEND) research initiative. ASCEND aims at assessing the feasibility of space data centers, envisioning data centers with an a capacity of 10MW.

In the future, the creation of Edge Nodes and SEC constellations could drastically simplify the OBDH architecture of satellite systems as most of the computation load could be transferred to a tiers platform.

## 6 Conclusion

In this article, we presented a definition of SEC for satellite systems orbiting the earth from the digital processing perspective. SEC architectures are composed of heterogeneous digital processing elements communicating through various interconnect means. COTS are more and more chosen as processing elements. Emerging technologies like AI and ISL are foreseen to play a central role in future data processing and data sharing between satellite systems. The described SEC architecture could be used for extraterrestrial missions around the Moon, Mars or in
deep space exploration. Our future search will try to investigate the digital pro-
cessing distribution in emerging SEC systems and propose a standardized SEC
architecture.

**Acknowledgement.** This work was financially supported by HARMONY European project (GRANT agreement ID: 101072798).

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