Towards AI Onboard EO Satellites: Assessment of Virtualization Techniques for Extreme Edge Computing

Extreme-edge computers coupled with sophisticated remote sensors are becoming a pivotal component for Earth Observation (EO) satellites. Such components benefit from the employment of virtualization techniques to enable the dynamic deployment of novel on-board Artificial Intelligence (AI) and to concurrently support multiple users on the same platform. This paper presents a comparative analysis of state-of-the-art virtualization techniques (namely Unikernels, Virtual Machines and Containers) specifically within the realm of AI-driven EO. Focused on five key criteria - security, scalability, resource efficiency, performance, and multitenancy - the study synthesizes existing literature to elucidate the strengths and limitations of each virtualization technology, and augments this understanding through a hands-on evaluation. Unikernels are distinguished for their minimalistic design and high efficiency, virtual machines for their robust isolation and stability, and containers for their flexibility. The comparative framework aims to guide engineers in selecting the most suitable virtualization technology according to the needs of their use case. This analysis clarifies the current state of virtualization technologies and provides a nuanced understanding of their applicability in advancing the capabilities of AI-driven EO systems.