Fabiana Rossi

Fabiana RossiI am a PhD Student in Computer Science, Control and GeoInformation (XXXIV Cycle) at the Dept. of Civil Engineering and Computer Science Engineering of the University of Rome Tor Vergata, Italy.

My research interests are in the field of distributed and Cloud computing systems, with a special focus on adaptation of container-based applications with Quality of Service requirements over geo-distributed infrastructures. In this field of research, I have co-authored 8 papers which have been published in international journals, conferences and workshops proceedings.
Here you can find my CV and a list of publications from Google Scholar.

Contact information

Fabiana Rossi
Dipartimento di Ingegneria Civile e Ingegneria Informatica, Stanza D1-19
Università degli Studi di Roma Tor Vergata
Via del Politecnico 1, 00133 Roma, Italy
e-mail: email address
ORCID: 0000-0002-5263-2208

Education

  • Sept 2020 - present: Visiting researcher at the Distributed System Group, headed by Schahram Dustdar, at TU Wien, Vienna, Austria.
  • Nov 2018 - present: PhD Student in Computer Science, Control and Geo- Information at the University of Rome Tor Vergata.
    Winner of a 3-year grant financed by the Italian Ministry for Education, University, and Scientific Research in 2018. Financial grant period: from November 2018 to October 2021.
  • October 2018 : Laurea Magistrale (master’s degree) cum laude in Computer Engineering at the University of Rome Tor Vergata.
    Thesis title (in Italian): Horizontal and Vertical Scaling of Container-based Applications using Reinforcement Learning. Advisor: Prof. Valeria Cardellini
  • October 2016: Laurea Triennale (bachelor's degree) cum laude in Computer Engineering at the University of Rome Tor Vergata.
Summer Schools
  • 2020: Participation to the 3rd Advanced Course on Data Science & Machine Learning (ACDL 2020), Siena, Italy, July 2020.
  • 2019: Selected for participating to the 2019 ACM Europe Summer School on HPC Computer Architectures for AI and Dedicated Applications. The Summer School took place on July 2019 in Barcelona, Spain. Selected 64 students out of 146 participants.
  • 2018: Selected for participating to the 2nd ACM Europe Summer School on Data Science, held in Athens, Greece, on July 2018. Selected 61 students out of 220 participants.

Awards and Acknowledgements

Honors and Awards
  • 2019: Winner of the Memory Compression Contest organized by the ACM Europe Summer School on HPC Computer Architectures for AI and Dedicated Applications.
  • 2017: Finalist at the CINI Smart City University Challenge, organized by Italian Inter-university Consortium for Computer Science (CINI) and co-located with the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017).
  • 2016: Winner of a student grant financed by MIUR (Italian Ministry for Education, University, and Scientific Research). First classified out of fifteen available positions, and selected among the top students enrolled in the academic year 2013/2014 in Engineering disciplines at the University of Rome Tor Vergata.
  • 2012: Honored as one of the top 300 Italian students that completed the school year 2011/12 with the highest grades. Contest organized by the Scuola Normale Superiore, Pisa, Italy
Research and Student Grants
  • 2020: Student Registration Grant supported by IEEE-TCI for attending the 1st IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2020), Washington, USA, August 2020.
  • 2020: Winner of a $ 1000 Google Cloud Research Credits for the research project entitled "Geo-distributed and Elastic deployment of containers in Kubernetes".
  • 2019: Student Travel Grant for attending the 2019 ACM Europe Summer School on HPC Computer Architectures for AI and Dedicated Applications, in Barcelona, Spain, July 2019.

Teaching

In the current academic year (2019/20), I teach the following courses:

In the past academic year (2018/19), I taught the following courses:

Publications

2020
  • IC F. Rossi, V. Cardellini, F. Lo Presti, "Self-adaptive threshold-based policy for microservices elasticity", In Proceedings of the 28th IEEE Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2020), Nice, France, November 17-19 2020.
  • IC F. Rossi, V. Cardellini, F. Lo Presti, "Hierarchical scaling of microservices in Kubernetes", In Proceedings of the 1st IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2020), Washington, DC, Washington, USA, August 17-21 2020. (doi, pdf)
  • IJ F. Rossi, V. Cardellini, F. Lo Presti, M. Nardelli, "Geo-distributed efficient deployment of containers with Kubernetes", Computer Communications, 14 pages, vol.159, pp.161--174, June 2020 (Elsevier)
  • IC F. Rossi, "Auto-scaling Policies to Adapt the ApplicationDeployment in Kubernetes", In Proceedings of the 12th ZEUS Workshop 2020 (ZEUS 2020), Potsdam, Germany, February 2020. First version available online.
2019
  • IC V. Cardellini, F. Lo Presti, M. Nardelli, F. Rossi, "Self-adaptive Container Deployment in the Fog: a survey", 5th International Symposium on Algorithmic Aspects of Cloud Computing (ALGOCLOUD 2019), Munich, Germany, September 10, 2019. Published in Lecture Notes in Computer Science Vol. 12041, Springer, pp. 77-102, August 2020. (doi, pdf)
  • IC F. Rossi, "Self-management of Containers Deployment in Decentralized Environments", In Proceedings of the 2019 IEEE World Congress on Services (SERVICES), pp. 315-318, Milan, Italy, July 8-13 2019. doi: 10.1109/SERVICES.2019.00088 (IEEE, pdf)
  • IC F. Rossi, V. Cardellini, F. Lo Presti, "Elastic Deployment of Software Containers in Geo-Distributed Computing Environments" In Proceedings of the 2019 IEEE Symposium on Computers and Communications (ISCC 2019), pp. 1-7, Barcelona, Spain, June 29-July 3 2019. (IEEE, pdf)
  • IC F. Rossi, M. Nardelli, V. Cardellini, "Horizontal and Vertical Scaling of Container-based Applications using Reinforcement Learning" In Proceedings of the 2019 IEEE International Conference on Cloud Computing (CLOUD 2019), pp. 329-338, Milan, Italy, July 8-13 2019. doi: 10.1109/CLOUD.2019.00061 (IEEE, pdf)
IC International Conference or Workshop Paper, IJ International Journal Paper, BC Book chapter.

Software

Rlad-core

Rlad-core is a Reinforcement Learning (RL) based Adaptive Deployment solution, which uses machine learning techniques to scale services. GitHub repository.