Tutorials

Abstract: Low Earth Orbit (LEO) satellites enable applications such as global internet connectivity, remote sensing, Earth observation, and scientific research, with significant growth driven by advancements in satellite miniaturization, lower launch costs, and increasing demand for broadband access. The integration of edge computing capabilities into LEO satellite systems gives rise to the new field of Orbital Edge Computing (OEC). OEC represents a transformative shift in space-based data processing, enabling real-time analytics, reduced latency, and enhanced autonomy in remote and bandwidth-constrained environments. In parallel with the development of OEC, Federated Learning (FL) emerged as a promising new approach in distributed machine learning by enabling model training across decentralized data sources without transferring raw data. This tutorial explores the architectural paradigms, technological enablers, and application domains of Federated Learning in Orbital Edge Computing. We review basic concepts of FL and an FL Framework (Flower) to provide hands-on experience with FL tools, followed by simulation integration and onboard processing considerations for LEO satellites.

Abstract: Serverless computing simplifies application development by abstracting infrastructure management, allowing developers to focus on functionality while cloud providers handle resource provisioning and scaling. However, orchestrating serverless workloads across the edge-cloud continuum presents challenges, from managing heterogeneous resources to ensuring low-latency execution and maintaining fault tolerance and scalability. These challenges intensify when scaling from lightweight functions to compute-intensive tasks such as large language model (LLM) inferences in distributed environments. This tutorial explores serverless computing's evolution from small functions to large-scale AI workloads, covering advanced orchestration strategies, multi-objective scheduling, and energy efficiency.