Associate Professor, IRISA / INSA Rennes
Address: IRISA / Inria Rennes – Bretagne Atlantique
Campus Universitaire de Beaulieu
35042, Rennes, France
Phone: + 33 2 99 84 75 66
E-mail: alexandru.costan at irisa.fr
My main research interests include Big Data management on large scale infrastructures like clouds, event streaming and workflow management. Relevant topics are:
- Big Data Analytics and High Performance Computing convergence;
- Geographically distributed data management for multi-site clouds;
- Efficient data management for workflows running on clouds;
- Hybrid infrastructures (clouds and dekstop grids, public and private clouds);
- MapReduce optimisations.
- Our paper “Tyr: Blob Storage Meets Built-In Transactions” was accepted for publication at ACM/IEEE SuperComputing’16 (Acceptance Rate: 17%), Best Student Paper Finalist
- Co-chair of the BigDataCloud’16 workshop, organised with IEEE Cluster 2016
- Co-chair of the ScienceCloud’16 workshop, organised with ACM HPDC 2016
- Our paper “Towards Multi-site Metadata Management for Geographically Distributed Cloud Workflows” was accepted for publication at IEEE Cluster 2015 (Acceptance Rate: 24%)
- Principal Investigator of the ANR OverFlow project, budget 250,000 EUR.
- Our paper “OverFlow: Multi-Site Aware Big Data Management for Scientific Workflows on Clouds” was accepted for publication in IEEE Transactions on Cloud Computing
- Our paper “JetStream: Enabling high throughput live event streaming on multi-site clouds” was accepted for publication in Future Generation Computer Systems
- Editor of the Soft Computing Journal Special Issue on: Autonomic Computing and Big Data Platforms
- Submission Chair of the of the IEEE Cluster 2014 conference
I am an Associate Professor at INSA Rennes. Until 2012 I was a postdoctoral researcher within the KerData team at Inria Rennes, working with dr. Gabriel Antoniu and prof. Luc Bougé, on scalable storage in cloud environments. In 2011 I obtained a Ph.D. in Computer Science from the Politehnica University of Bucharest, Romania, where my advisor was prof. Valentin Cristea. My Ph.D. thesis was focused on self-adaptive behavior of large-scale distributed systems based on monitoring information, bringing several contributions to the MonALISA monitoring system.
- JetStream is a high performance batch-based streaming middleware. The system is able to self-adapt to the streaming conditions by modeling and monitoring a set of context parameters. It further aggregates the available bandwidth by enabling multi-route streaming across cloud sites.
- TomusBlobs is a concurrency-optimized data storage system which federates the virtual disks associated to the Virtual Machines running the application code on the cloud. It is used in the Azure cloud for efficient data-intensive processing based on MapReduce.
- MonALISA, which stands for Monitoring Agents using a Large Integrated Services Architecture, has been developed over the last years by Caltech and its partners with the support of the U.S. CMS software and computing program. The framework is based on Dynamic Distributed Service Architecture and is able to provide complete monitoring, control and global optimization services for complex systems.
- Z-CloudFlow (2013-2016): geographically distributed workflows on Azure clouds. A project of the Microsoft-Inria Joint Research Centre.
- BigStorage (2015-2018) is an European Training Network (ETN) project. Area: Storage-based Convergence of HPC and Cloud infrastructures to handle Big Data. Role: local coordinator for Inria Rennes Bretagne Atlantique.
Former PhD Students
- Radu Tudoran now at Huawei European Research Center, Germany