Multi-Agent Adaptive Architecture for Flexible Distributed Real-Time Systems
Recent critical embedded systems become more and more complex and usually react to their environment that requires to amend their behaviors by applying run-time reconfiguration scenarios. A system is defined in this paper as a set of networked devices, where each of which has its own operating syste...
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Veröffentlicht in: | IEEE access 2018-01, Vol.6, p.23152-23171 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Recent critical embedded systems become more and more complex and usually react to their environment that requires to amend their behaviors by applying run-time reconfiguration scenarios. A system is defined in this paper as a set of networked devices, where each of which has its own operating system, a processor to execute related periodic software tasks, and a local battery. A reconfiguration is any operation allowing the addition-removal-update of tasks to adapt the device and the whole system to its environment. It may be a reaction to a fault or even optimization of the system functional behavior. Nevertheless, such scenario can cause the violation of real-time or energy constraints, which is considered as a critical run-time problem. We propose a multi-agent adaptive architecture to handle dynamic reconfigurations and ensure the correct execution of the concurrent real-time distributed tasks under energy constraints. The proposed architecture integrates a centralized scheduler agent (ScA) which is the common decision making element for the scheduling problem. It is able to carry out the required run-time solutions based on operation research techniques and mathematical tools for the system's feasibility. This architecture assigns also a reconfiguration agent (RA p ) to each device p to control and handle the local reconfiguration scenarios under the instructions of ScA. A token-based protocol is defined in this case for the coordination between the different distributed agents in order to guarantee the whole system's feasibility under energy constraints. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2018.2825023 |