Dynamic Reconfiguration of Intelligence for High Behaviour Adaptability of Autonomous Distributed Discrete-Event Systems

This paper deals with the intelligence adaptation of distributed real-time embedded control systems when scenarios of reconfiguration happen in their hardware or software level. The reconfiguration process is a composition of controllers reconfiguration by adding/deleting or updating tasks and intelligence reconfiguration by adding/deleting and updating the rule base. The system architecture is composed of an application layer implemented as the real-time periodic tasks and an intelligence layer for autonomous and adaptive control behavior. In this research work, a rule-based system is used as the artificial intelligence component, where we propose to optimize the inference process by splitting the rule base into two sub-bases; the effective one and the general meta base. With this facility, the coordination in decision making for the distributed platform and system Quality of Service (QoS) in complex and robust system implementation should be faced by new strategies and correct policies. In this sense, we propose a new protocol for the coordination in the two levels of the reconfiguration process to get correctness in the system results. Dealing with performance, we propose to supervise the intelligence QoS of the whole distributed system. Also, we present the correctness of the coordination between the different decisions by the field of the coordination factor. An implementation of the paper contribution with Drools as an integrated rule-based system framework to RTDroid and a discussion of the inferring time and the memory consumption are presented in this paper.