Abstract: Cloud Computing during the time has gained concrete evidence to be a disruptive technology still in its full development. Many drawbacks of the Cloud have brought to improve many their crucial aspects, like performance, security and privacy, etc. Today Edge Computing try to deal with these implications to make them less problematic and much more feasible. Starting from the NIST definition (IaaS, PaaS and SaaS), the talk looks at the last decade of ICT evolution preparing the systems for new ICT challenges and implementations, like AI algorithms on top of them.
Lecturer Short CV: Lorenzo Carnevale is an assistant professor in the Future Computing Research Laboratory at the Department of Mathematics, Computer Science, Physics and Hearth Sciences of the University of Messina. He was research fellow in the same university and he earned my Ph.D. in the Department of Engineering at University of Reggio Calabria in May 2020 under the supervision of Massimo Villari. He led activities related to the technical area for the Horizon 2020 project “FLIWARE” and the Italian FISR “Re-functionalization of the Contemporary”. From 2018 to 2020, he worked as software developer of Humanizing Technologies GmbH in Vienna, one of the most appreciated suppliers of non-industrial robots and robot software worldwide. From 2020, He is an AWS Certified Cloud Practitioner. From 2021, he is authorized to practice as Information Engineer (Italy, Section A). From 2022, he led activities related to artificial intelligence in federated cloud/edge environments for the Horizon Europe TEMA project. From 2023, he led the activitie related to the artificial intelligence optimization for microcontrollers for the Horizon Europe NEUROKIT2E project. He has been teacher of Algorithms and Computational Intelligence classes. I am reviewer of respected Springer, IEEE and Elsevier Journals, member of the CINI InfoLife Laboratory and IFIP Working Group 12.9 about Computational Intelligence, Associate Editor for Frontiers in Robotics and AI and MDPI Machine Learning and Knowledge Extraction, co-chairs of IEEE Workshops (DistInSys, MrICHE, and AI4Health), program chair of UCC 2023 and FLTA 2024 and co-author of more than 50 manuscripts.