Towards an Adaptive Supervision of Distributed Systems

The traditional, centralized, approach to supervision is challenged when communications between supervision and supervised systems become either slow, disrupted or too costly. To obtain a supervision system that is able to dynamically adapt itself to the communications’ state, we propose to distribute the supervision process through several autonomous agents. To evaluate our approach, we made experiments on a simulator for distributed systems using three different supervision approaches. Results show that our agent’s decision model does lead to a relevant autonomous supervision in distributed systems where a short response time prevails over a limited repair extra-cost.