Research Interests:

I am interested in Distributed Constraint Reasoning (DCR). DCR is a framework for solving various problems arising in Distributed Artificial Intelligence. In DCR, a problem is expressed as a Distributed Constraint Network (DCN). A DCN is composed of a group of autonomous agents where each agent has control of some elements of information about the problem, that is, variables and constraints. Each agent own its local constraint network. Variables in different agents are connected by constraints.

Agents try to find a local solution (locally consistent assignment) and communicate it with other agents using a DCR protocol to check its consistency against constraints with variables owned by other agents. A DCN offers an elegant way to model and solve naturally distributed constraint satisfaction/optimization problems that are distributed by nature (e.g., distributed resource allocation, distributed meeting scheduling, sensor networks, etc).


Globally Optimized Energy Efficient Data Centres:

My current research work involves optimizing workload allocation across a geographically distributed data centres such that total energy cost is minimized, as part of the EU FP7-Transport funded project (GENiC). Geographically distributed data centres (GDDC) presents many possible benefits in terms of reducing energy costs through global, rather than local, optimisation. In particular each location may have different unit energy costs, external weather conditions, local renewable sources, etc. Therefore reasoning at a global level can exploit these differences through optimally reallocating workload in each time period through migration of virtual machines, subject to constraints on number of migrations, virtual machine sovereignty, data centre capacities, etc. The GDDC is a naturally distributed resource allocation problem where data centres may not be willing to reveal their private information to other data centres. In addition, sending the whole knowledge about the problem to a centralized location will create a bottleneck on the communication towards that location. Thus, a distributed solving process is preferred for the geographically distributed data centres problem.

Conference activities:

Program committee member:

  • International Conference on Principles and Practice of Constraint Programming (CP): CP'2017
  • International Workshop on Optimisation in Multi-agent Systems (OPTMAS): OPTMAS'2015, OPTMAS'2016, OPTMAS'2017
  • Journées Francophones de Programmation par Contraintes (JFPC): JFPC'2014, JFPC'2016, JFPC'2017
  • Doctoral Program of International Conference on Principles and Practice of Constraint Programming (DPCP): DPCP'2016
  • The International Symposium On Ubiquitous Networking: (UNet): UNet’2015


Research activities:

I was a member of the research team TASC (Theory, Algorithms, and Systems for Constraints). TASC is a joint team of the INRIA's research center of Rennes and of the CNRS's computer science laboratory of Nantes-Atlantique (LINA).

During my Ph.D. thesis (2009-2012), I was a member of the Coconut team (Constraints, Learning and Agents.

Organizing Committee Member:

Student Volunteers on the Organising Committee of the European Conference on Artificial Intelligence 2012 (ECAI'12).

Professional memberships: