Machine Learning Platform for Extreme Scale Computing on Compressed IoT Data

Tirupathi, Seshu; Salwala, Dhaval; Zizzo, Giulio; Rawat, Ambrish; Purcell, Mark; Jensen, Søren Buus; Thomsen, Christian; Ho, Nguyen; Cuza, Carlos Enrique Muniz; Brusokas, Jonas; Pedersen, Torben Bach; Alexiou, George; Giannopoulos, Giorgos; Gidarakos, Panagiotis; Kalimeris, Alexandros; Maroulis, Stavros; Papastefanatos, George; Psarros, Ioannis; Stamatopoulos, Vassilis; Terrovitis, Manolis

doi:10.1109/bigdata55660.2022.10020540

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Cited by 3 publications

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Holistic Analytics of Sensor Data from Renewable Energy Sources: A Vision Paper

Jensen,

Thomsen

2023

Communications in Computer and Information Science

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Modern Renewable Energy System (RES) installations, e.g., wind turbines, produce petabytes of high-frequency time series. State-of-the-art systems cannot cope with such amounts of data. Thus, practitioners generally store simple aggregates, e.g., 10-min averages. Based on discussions with practitioners, we present requirements and our vision for a next-generation time series management system that can efficiently manage vast amounts of time series across edge, cloud, and client.

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