Daniel Rosendo – KerData

Ph.D. Candidate

Contact details

IRISA / Inria Rennes – Bretagne Atlantique
Office: D174
Campus Universitaire de Beaulieu
35042, Rennes, France

Phone: +33 7 49 11 91 68
E-mail: daniel.rosendo at inria.fr

Research Interests

Deployment of Edge-to-Cloud workflows on large scale distributed infrastructures
Reproducibility and Provenance of Edge-to-Cloud workflows
Performance optimization of Edge-to-Cloud workflows

Ph.D. Topic

Enabling Reproducible Analysis of Complex Application Workflows on the Edge-to-Cloud Computing Continuum (funded by: Inria Project Lab (IPL) HPC-BigData)

Short Bio

Daniel Rosendo is a Ph.D. candidate at Inria in Rennes, within the KerData team since October 2019, under the supervision of Alexandru Costan (INSA Rennes), Gabriel Antoniu (Senior scientist at Inria in Rennes), and Patrick Valduriez (Senior scientist at Inria in Montpellier). His Ph.D focus on enabling reproducible analysis of complex application workflows on the Edge-to-Cloud Computing Continuum. His recent research interests include Cloud and Edge Computing, reproducibility, and optimization.

Teaching

INSA Rennes: Big Data Algorithms – lectures and practical sessions on Apache Flink (7.5h/year, since 2020)
MIAGE Master of the University Rennes 1: Cloud for Big Data module – practical sessions on Apache Hadoop (24h/year, since 2019).

Publications

A list of publications can be found on Google Scholar.

Software

E2Clab: is a framework that implements a rigorous methodology for designing experiments with real-world workloads on the Edge-to-Cloud Computing Continuum. This methodology provides guidelines to move from real-world use cases to the design of relevant testbed setups for experiments enabling researchers to understand performance and to support the reproducibility of the experiments.