Publications

My academic peer-reviewed publications.

2024

Vincenzo De Maio, Meerzhan Kanatbekova, Felix Zilk, Nicolai Friis, Tobias Guggemos, Ivona Brandic: Training Computer Scientists for the Challenges of Hybrid Quantum-Classical Computing. IEEE/ACM CCGrid 2024 arXiv preprint
Sabrina Herbst, Vincenzo De Maio, Ivona Brandic: On Optimizing Hyperparameters for Quantum Neural Networks. ArXiv
Sandeep Suresh Cranganore, Vincenzo De Maio, Ivona Brandic, Ewa Deelman: Paving the Way to Hybrid Classic-Quantum Scientific Workflows. Elsevier Future Generation Computer Systems (accepted for publication). Arxiv preprint

Sabrina Herbst, Vincenzo De Maio, Ivona Brandic: Streaming IoT Data and the Quantum Edge: A Classic/Quantum Machine Learning Use Case. IEEE QuickPar@EuroPar 2023. arXiv preprint
Sabtain Ahmad, Halit Uyanik, Tolga Ovatman, Mehmet Tahir Sandikkaya, Vincenzo De Maio, Ivona Brandic, Atakan Aral: Sustainable Environmental Monitoring via Energy and Information Efficient Multinode Placement. IEEE Internet Things J. 10(24): 22065-22079 (2023)
Shashikant Ilager, Vincenzo De Maio, Ivan Lujic, Ivona Brandic: Data-centric Edge-AI: A Symbolic Representation Use Case. EDGE 2023: 301-308
Vincenzo De Maio, Ivona Brandic: Accelerating Scientific Applications with the Quantum Edge: A Drug Design Use Case. ISC Workshops 2023: 134-143

Ivan Lujic, Vincenzo De Maio, Srikumar Venugopal, Ivona Brandic: SEA-LEAP: Self-Adaptive and Locality-Aware Edge Analytics Placement. IEEE Trans. Serv. Comput. 15(2): 602-613 (2022)
Atakan Aral, Vincenzo De Maio, Ivona Brandic: ARES: Reliable and Sustainable Edge Provisioning for Wireless Sensor Networks. IEEE Trans. Sustain. Comput. 7(4): 761-773 (2022)
Sandeep Suresh Cranganore, Vincenzo De Maio, Ivona Brandic, Tu Mai Anh Do, Ewa Deelman: Molecular Dynamics Workflow Decomposition for Hybrid Classic/Quantum Systems. e-Science 2022: 346-356
Josip Zilic, Vincenzo De Maio, Atakan Aral, Ivona Brandic: Edge offloading for microservice architectures. EdgeSys@EuroSys 2022: 1-6
Vincenzo De Maio, Atakan Aral, Ivona Brandic: A Roadmap To Post-Moore Era for Distributed Systems. ApPLIED@PODC 2022: 30-34
Vincenzo De Maio, David Bermbach, Ivona Brandic: TAROT: Spatio-Temporal Function Placement for Serverless Smart City Applications. UCC 2022: 21-30

Ivan Lujic, Vincenzo De Maio, Klaus Pollhammer, Ivan Bodrozic, Josip Lasic, Ivona Brandic: Increasing Traffic Safety with Real-Time Edge Analytics and 5G. EdgeSys@EuroSys 2021: 19-24

Vincenzo De Maio, Dragi Kimovski: Multi-objective scheduling of extreme data scientific workflows in Fog. Future Gener. Comput. Syst. 106: 171-184 (2020)
Ennio Torre, Juan José Durillo, Vincenzo De Maio, Prateek Agrawal, Shajulin Benedict, Nishant Saurabh, Radu Prodan: A dynamic evolutionary multi-objective virtual machine placement heuristic for cloud data centers. Inf. Softw. Technol. 128: 106390 (2020)
Ivan Lujic, Vincenzo De Maio, Ivona Brandic: Resilient Edge Data Management Framework. IEEE Trans. Serv. Comput. 13(4): 663-674 (2020)
Alfredo Cuzzocrea, Vincenzo De Maio, Edoardo Fadda: Experimenting and Assessing a Distributed Privacy-Preserving OLAP over Big Data Framework: Principles, Practice, and Experiences. COMPSAC 2020: 1344-1350

Vincenzo De Maio, Rafael Brundo Uriarte, Ivona Brandic: Energy and Profit-Aware Proof-of-Stake Offloading in Blockchain-based VANETs. UCC 2019: 177-186
Vincenzo De Maio, Ivona Brandic: Multi-Objective Mobile Edge Provisioning in Small Cell Clouds. ICPE 2019: 127-138

Vincenzo De Maio, Ivona Brandic: First Hop Mobile Offloading of DAG Computations. CCGrid 2018: 83-92
Ivan Lujic, Vincenzo De Maio, Ivona Brandic: Adaptive Recovery of Incomplete Datasets for Edge Analytics. ICFEC 2018: 1-10

Ivan Lujic, Vincenzo De Maio, Ivona Brandic: Efficient Edge Storage Management Based on Near Real-Time Forecasts. ICFEC 2017: 21-30
Giuseppe Caggianese, Mariaconsiglia Calabrese, Vincenzo De Maio, Giuseppe De Pietro, Armando Faggiano, Luigi Gallo, Giovanna Sannino, Carmine Vecchione: A Rehabilitation System for Post-operative Heart Surgery. IIMSS 2017: 554-564

Vincenzo De Maio, Radu Prodan, Shajulin Benedict, Gabor Kecskemeti: Modelling energy consumption of network transfers and virtual machine migration. Future Gener. Comput. Syst. 56: 388-406 (2016)
Vincenzo De Maio, Gabor Kecskemeti, Radu Prodan: An Improved Model for Live Migration in Data Centre Simulators. CCGrid 2016: 527-530
Vincenzo De Maio, Gabor Kecskemeti, Radu Prodan: An improved model for live migration in data centre simulators. UCC 2016: 108-117

Vincenzo De Maio, Gabor Kecskemeti, Radu Prodan: A Workload-Aware Energy Model for Virtual Machine Migration. CLUSTER 2015: 274-283

Vincenzo De Maio, Vlad Nae, Radu Prodan: Evaluating Energy Efficiency of Gigabit Ethernet and Infiniband Software Stacks in Data Centres. UCC 2014: 21-28