Flotilla: A scalable, modular and resilient federated learning framework for heterogeneous resources
Abstract
We introduce Flotilla, a flexible and lightweight FL platform designed for real-world edge environments, offering modular strategy support, asynchronous updates, and high fault tolerance. It runs efficiently on edge hardware like Raspberry Pi and Jetson, outperforming or matching top frameworks like Flower, OpenFL, and FedML, while scaling seamlessly to 1000+ clients.
🧩 My Contribution
I was closely involved in the design and development of Flotilla, contributing to the overall architecture, implementation of core components, and evaluation of system behavior under both standard and failure conditions.
I co-authored the initial drafts of the paper, focusing on articulating the systems perspective — including modular design, fault tolerance, and large-scale deployment challenges.
My work spanned design discussions, implementation sprints, and benchmarking, helping shape Flotilla from concept to a functioning, scalable framework.
