Search results

Li, N. (2025). Data quality control and research asset discovery for open science. [Thesis, fully internal, Universiteit van Amsterdam].
Wang, Y., Tripathi, S., Farshidi, S., & Zhao, Z. (2025). D-VRE: From a Jupyter-enabled Private Research Environment to Decentralized Collaborative Research Ecosystem. Blockchain: Research and Applications, 6(1), Article 100244. https://doi.org/10.1016/j.bcra.2024.100244
Hsu, C., Martín-Pérez, J., Papagianni, C., & Grosso, P. (2024, September 25). Dataset for Elastic Resource Scaling [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13838059
Hsu, C., De Vleeschauwer, D., & Papagianni, C. (2024, September 25). Dataset for SLAs Decomposition [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13837936
Farshidi, S., & Steffens, L. (2024, June 26). Data-Driven Decision Model for Machine Learning Model Selection [Data set]. Mendeley Data. https://doi.org/10.17632/drh9669vc3.1
Pan, R., Shi, Z., Belloum, A., & Zhao, Z. (2024). Operating ZKPs on Blockchain: A Performance Analysis Based on Hyperledger Fabric. In 2024 IEEE International Conference on Decentralized Applications and Infrastructures: DAPPS 2024 : proceedings : 15-18 July 2024, Shanghai, China (pp. 69-78). IEEE Computer Society. https://doi.org/10.1109/DAPPS61106.2024.00018
Dimoglis, A., Alhamed, F., Dalgkitsis, A., Sgambelluri, A., Paolucci, F., Papagianni, C., & Grosso, P. (2024). In-network Control for Flow Steering. In F. Prudenzano, & M. Marciniak (Eds.), 24th ICTON 2024 - International Conference on Transparent Optical Networks: July 14th-18th, 2024, Bari, Italy : conference proceedings (pp. 290-293). IEEE. https://doi.org/10.1109/ICTON62926.2024.10647782
Grosso, P. (2024). Connected.
Cheng, L., Wang, Y., Cheng, F., Liu, C., Zhao, Z., & Wang, Y. (2024). A Deep Reinforcement Learning-Based Preemptive Approach for Cost-Aware Cloud Job Scheduling. IEEE Transactions on Sustainable Computing, 9(3), 422-432. https://doi.org/10.1109/TSUSC.2023.3303898
Xin, R., Chen, P., Grosso, P., & Zhao, Z. (2024). A fine-grained robust performance diagnosis framework for run-time cloud applications. Future Generation Computer Systems, 155, 300-311. https://doi.org/10.1016/j.future.2024.02.014

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