Orchestrating Serverless Applications in the Edge Cloud Space Continuum: What Breaks and What is Next?

TL;DR

This paper analyzes the challenges of extending serverless computing to the edge cloud space continuum, especially in LEO satellite networks, and proposes an architecture to address these issues.

Contribution

It identifies ten broken assumptions in existing orchestration methods and introduces a new architecture tailored for dynamic, constraint-aware edge environments.

Findings

Identified ten broken assumptions in current serverless orchestration.

Organized challenges into three core categories: dynamic graphs, constraints, and decentralized correctness.

Proposed an architecture demonstrated through a flood response use case.

Abstract

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.