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Eric RuttenResearcher at INRIA+33 4 76 61 55 50mail web
Tayeb BouhadinaPost-doc +33 4 76 61 .. ..mail
Xin AnPhD Student
co-advised with A. Gamatie (Lille)
+33 4 76 61 .. ..mail
Sebastien GuilletPhD Student
co-advised with F. de Lamotte (Lorient)
+33 2 97 87 45 60mail
Soguy GeyeMasters student (MOSIG, Grenoble)
co-advised with N. de Palma


The BZR language works and is available, to program reactive controllers, in a mixed imperative/declarative style

Context: adaptive and reconfigurable computing systems

Computing systems are called adaptive, reconfigurable, or also autonomic, when they feature software and hardware that is able to:

The motivations for adaptation concern generally self-management of aspects like energy/power consumption, battery charge, processor heating, wifi coverage, local communication protocol; tasks and computing resources management (memory, CPU, time); quality of service, variants and versions, user events; variability, at fabrication or over life-time, of multi-processor SoC; dependability, fault-tolerance by switching between redundant processes.

Adaptation can be considered and managed at different levels: application, software infrastructure (middleware, OS), architecture (hardware) or environment. It can also be envisaged at different moments, like design-time (program specialization), deployment-time, and run-time. It can even be considered at a higher level, with adaptation of the controller itself, at run-time, in an upper-level loop changing the adaptation policy itself. This kind of generation of a new controller is especially feasible for slow paced systems e.g., adding a new device in a home system, at a days-scale.

Application domains can be found in: embedded systems, open (sensor networks) or not (safety-critical), domotics and building automation, telecommunications and mobile devices, scientific computation and grid computing, web and service oriented architectures.

Existing techniques for the control of adaptation are very diverse, and can feature ad hoc programming, rule-based systems (with heuristics, learning, AI techniques, ...), analytical and predictive models of the regulation object, ...

We are particularly interested in techniques related to control theory based on models of the dynamics, which can be either continuous, or discrete, or hybrid.

Approach: Model-based Control

Our approach is to apply control techniques based on the behavioral model of reactive automata and the algorithmic techniques of discrete controller synthesis. We consider the problem theoretically and also concretely, and we therefore adopt the synchronous approach to reactive systems: this way we can, on the one hand, rely on synchronous languages as modeling formalism, equipped with compilers and executable code generators, and on the other hand, use an associated effective controller synthesis tool: Sigali. Both are integrated into a programming language, called BZR, and its compiler, as an extension of the Heptagon language. We thus have a complete tool-supported method from control modeling down to concrete execution, considering different execution models, and targetting either software or hardware.

This gives us a multi-tier approach to the model-based control of adaptive computing systems, where we can consider the general problem, and contribute on a more specialized topic: to model the discrete behaviours of the system to be regulated, and to obtain a correct controller by automated synthesis.

The originality of our approach is in the emerging nature of this topic in computer science, which is appearing in soft-, hard- and middleware. It represents a new combination of existing approaches in :

We explore control theory for computer science, as an original alernative to computer science for control (as more usually in embedded systems), and to classical discrete control theory (as more usually applied to manufacturing).


We currently have the following activities and contacts on the different aspects of our approach:

Past participants

Gwenaƫl DelavalPost-doc at INRIA; now assistant Prof. at UJFmailweb
Ashutosh Katiyar intern (from IIT Delhi, India)
Soufyane AboubekrPhD student
Amine BelhadjMaster student (co-advised with ENSI Tunis)