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This paper analyzes the challenges of extending serverless computing to Low Earth Orbit (LEO) satellite constellations, identifying ten key assumptions broken by the dynamic and constrained nature of this environment. It organizes these challenges into three core areas: spatiotemporal execution, constraint-aware resource management, and decentralized state management. The paper then proposes a novel architecture for robust serverless execution across the edge cloud space continuum, validated through a flood response use case.
Serverless orchestration falls apart when you move it to space, but this paper proposes a new architecture to fix it.
Serverless computing has matured into an effective execution model for edge cloud environments, enabling function level decomposition, demand driven scaling, and workflow execution across stable, well provisioned infrastructure. This success motivates extending it to the edge cloud space continuum, where Low Earth Orbit (LEO) constellations are increasingly explored as distributed compute substrates. However, existing serverless orchestration is not directly applicable in this setting, where LEO systems impose time varying contact graphs, intermittent link availability, and strict feasibility constraints on energy, memory, communication, and operational cost. This article identifies ten broken assumptions in existing serverless orchestration and organizes them into three core challenges: spatiotemporal execution over dynamic graphs, constraint aware function placement and scaling, and correctness and progress under decentralized and delayed state. It then proposes an architecture that enables robust and efficient serverless execution across the continuum, grounded in these challenges and demonstrated through a representative flood response use case.
