@inproceedings{e5ae3d6f80ac451888b864fda9f6ea5d,
title = "FLORA: Federated Learning for Optimized Resource Allocation in Cinco de Bio",
abstract = "We introduce Federated Learning for Optimizing Resource Allocation (FLORA), an extension to the CINCO de Bio (CdB) 1 platform for health analysis workflows. FLORA uses Federated Learning (FL) to optimize resource allocation for Service-Independent Building Blocks (SIBs) execution across multiple CdB deployments, predicting maximum memory usage while maintaining privacy. Preliminary results from a matrix multiplication experiment demonstrate the potential of machine learning models to predict peak memory usage of a SIB. We outline the FLORA architecture, discuss its implementation within CdB, and propose future work to validate and integrate the framework in real-world settings.",
keywords = "Bayseian Machine Learning, Federated Learning, Health Informatics, Low-Code, No-Code, Resource Allocation Optimisation",
author = "Colm Brandon and Mashal Khan and Tiziana Margaria",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 49th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2025 ; Conference date: 08-07-2025 Through 11-07-2025",
year = "2025",
doi = "10.1109/COMPSAC65507.2025.00337",
language = "English",
series = "Proceedings - 2025 IEEE 49th Annual Computers, Software, and Applications Conference, COMPSAC 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2404--2405",
editor = "Hossain Shahriar and Alam, \{Kazi Shafiul\} and Hiroyuki Ohsaki and Stelvio Cimato and Miriam Capretz and Shamem Ahmed and Ahamed, \{Sheikh Iqbal\} and Majumder, \{AKM Jahangir Alam\} and Munirul Haque and Tomoki Yoshihisa and Alfredo Cuzzocrea and Michiharu Takemoto and Nazmus Sakib and Marwa Elsayed",
booktitle = "Proceedings - 2025 IEEE 49th Annual Computers, Software, and Applications Conference, COMPSAC 2025",
}