Sites Inria

Version française

SUMO Research team

SUpervision of large MOdular and distributed systems

Team presentation

The SUMO team proposes to combine formal methods approaches with concurrency theory, in order to address the modeling, analysis and management of large distributed or modular systems exhibiting quantitative aspects. Large distributed softwares and systems are indeed calling for quantitative models involving time, probabilities, costs, and combinations of them. As many problems in this setting become untractable or even undecidable, we are interested in the design of efficient approximation techniques, for example borrowed from electrical engineering approaches to the management of large stochastic systems.

Research themes

A strong point of SUMO is to gather skills from formal methods, discrete event systems, concurrency theory, and electrical engineering. Several application fields are covered: telecommunication networks management, modeling and verification of web services, control issues in large data centers, plus more opportunistic applications in the field of embedded systems or biological pathways.

International and industrial relations


  • AVerTS Indo-French project on the algorithmic verification of real-time systems
  • QuantProb Associated team on optimization of non-standard quantitative properties in partially observable probabilistic models with Dresden Technical University
  • EQUAVE Associated team on efficient quantitative verification.
  • ANR Project STOCH-MC (2014-2018), Stochastic Models: Scalable Model Checking.
  • P22 Project (2015-2018), Industrial project with Alstom Transport
  • ANR Headwork (2016-2020), Human-Centric Data Oriented Workflows
  • Softwarisation of everything: A joint resserach team within the INRIA-Nokia Bell Labs common lab, dedicated to programmability and management of SDNs


Keywords: Supervision Distributed system Cyber-physical system Model-checking Formal method Security Automatic Algorithmic. Logic . Optimization. Information theory. Game Theory