Gabriele Russo Russo

I am a Research Associate at the University of Rome Tor Vergata, in Italy, where I received my PhD degree in May 2021.

My research interests span the area of distributed computing systems with emphasis on performance optimization and run-time self-adaptation. As a PhD student, I investigated auto-scaling solutions for data stream processing applications, combining Reinforcement Learning techniques and traditional performance modeling tools.

Here is my CV and a list of publications (also available in DBLP).

Contact information

Dipartimento di Ingegneria Civile e Ingegneria Informatica
Università di Roma “Tor Vergata”
Via del Politecnico 1, 00133 Roma, Italy
russo.russo (at) ing.uniroma2.it

News

Recent publications

A. Alnafessah, G. Russo Russo, V. Cardellini, G. Casale, F. Lo Presti
AI-driven Performance Management in Data-Intensive Applications
In Communications Network and Service Management in the Era of Artificial Intelligence and Machine Learning, N. Zincir-Heywood, Y. Diao, M. Mellia (eds.) (To appear)
abstract

G. Russo Russo, V. Cardellini, F. Lo Presti, M. Nardelli
Towards a Security-aware Deployment of Data Streaming Applications in Fog Computing
In Fog/Edge Computing for Security,Privacy, and Applications, W. Chang and J. Wu (eds.)
abstract doi pdf

G. Russo Russo, V. Cardellini, G. Casale, F. Lo Presti
MEAD: Model-based Vertical Auto-Scaling for Data Stream Processing
Proc. of IEEE/ACM CCGRID ‘21
abstract doi

G. Russo Russo, V. Cardellini, F. Lo Presti
Reinforcement learning based policies for elastic stream processing on heterogeneous resources
Proc. of DEBS 2019
abstract doi

You can find here a list of all my publications.