2024
[11] Talia, D, Trunfio, P, Marozzo, F, Belcastro, L, Cantini, R, Orsino, A, “Programming Big Data Applications: Scalable Tools and Frameworks for Your Needs“. ISBN: 978-1-80061-504-5. World Scientific, 2024.
[10] Cantini, R, Marozzo, F, Orsino, A, Talia, D, Trunfio, P, Badia, RM, Ejarque, J, Vazquez, F, “Block size estimation for data partitioning in HPC applications using machine learning techniques”. In: Journal of Big Data 11, 19. (2024).
2023
[9] Belcastro, L, Marozzo, F, Orsino, A, Talia, D, Trunfio, P, “Using the Compute Continuum for Data Analysis: Edge-cloud Integration for Urban Mobility”. In: 2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). 2023, pp. 338–344.
[8] Belcastro, L, Marozzo, F, Orsino, A, Talia, D, Trunfio, P, “Edge-Cloud Continuum Solutions for Urban Mobility Prediction and Planning”. In: IEEE Access 11 (2023).
[7] Cantini, R, Marozzo, F, Orsino, A, “Deep Learning meets Smart Agriculture: using LSTM Networks to handle anomalous and missing sensor data in the Compute Continuum”. In: Device-Edge-Cloud Continuum – Paradigms, Architectures and Applications. 2023.
[6] Marozzo, F, Orsino, A, Trunfio, P, Talia, D, “Scaling machine learning at the edge-cloud: a distributed computing perspective”. In: 19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2023). 2023.
[5] Orsino, A, Cantini, R, Marozzo, F, “Evaluating the performance of a multimodal speaker tracking system at the edge-to-cloud continuum”. In: Device-Edge-Cloud Continuum – Paradigms, Architectures and Applications. 2023.
2022
[4] Belcastro, L, Cantini, R, Marozzo, F, Orsino, A, Talia, D, Trunfio, P, “Programming big data analysis: principles and solutions”. In: Journal of Big Data 9, 4 (2022).
[3] Belcastro, L, Marozzo, F, Orsino, A, “Hybrid edge/cloud solutions for supporting autonomous vehicles”. In: Autonomous Vehicles and Systems. River Publishers, 2022, pp. 255–268.
[2] Marozzo, F, Orsino, A, Talia, D, Trunfio, P, “Edge Computing Solutions for Distributed Machine Learning”. In: 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress. IEEE. 2022.
2021
[1] Cantini, R, Marozzo, F, Orsino, A, Talia, D, Trunfio, P, “Exploiting machine learning for improving in-memory execution of data-intensive workflows on parallel machines”. In: Future Internet 13.5 (2021).