Abstract: To determine system settings for an industrial system, digital twin data of a digital twin of the industrial system is retrieved. System simulations of the industrial system are performed based on the digital twin data to explore candidate system settings for the industrial system prior to application of one of the candidate system settings to the industrial system. At least one optimization objective or at least one constraint used in the system simulations is changed while the system simulations are being performed on an ongoing basis. The results of the system simulations are used to identify one of the candidate system settings for application to the industrial system.

Abstract: A method for detecting system problems in a distributed control system including a plurality of computational devices is suggested. The method includes:—deploying one or more software agents on one or more devices of the system;—monitoring, via the one or more software agents, a system configuration and/or a system functionality;—detecting a problem in the monitored system configuration and/or a system functionality;—adding one or more new software agents and deploying the one or more new software agents on one or more devices of the system associated with the problem;—collecting data associated with the problem, via the added software agents.

Abstract: A method for adjusting machine learning models in a system including a plurality of devices is suggested. The method includes providing a system including a plurality of devices, wherein the devices have computational resource capacities; providing one or more machine learning tasks; providing a repository of ML models for the one or more tasks, wherein a plurality of the ML models of a single task solve the same task with different computational resources requirements and different quality metrics; selecting a device of the plurality of devices of the system to execute a task, wherein the selected device has available computational resource capacities; and selecting, from the repository of ML models of the task to be executed, one of the ML models, wherein the computational resources requirements of the selected ML model do not exceed the available computational resource capacities of the selected device. Systems configured to perform the methods as disclosed herein are also suggested.

Abstract: A method for allocating fog applications in a fog network with a plurality of fog nodes is suggested. The method includes: providing an application model; providing a fog network image that reflects the properties of the fog network; performing a resource usage test of the application model on the fog network image, and receiving resource requirements for the fog network; creating a concrete application model based on the application model, wherein the concrete application model contains the received resource requirements; and performing allocation of the concrete application model on one or more of the fog nodes of the fog network.

Abstract: To determine system settings for an industrial system, digital twin data of a digital twin of the industrial system is retrieved. System simulations of the industrial system are performed based on the digital twin data to explore candidate system settings for the industrial system prior to application of one of the candidate system settings to the industrial system. At least one optimization objective or at least one constraint used in the system simulations is changed while the system simulations are being performed on an ongoing basis. The results of the system simulations are used to identify one of the candidate system settings for application to the industrial system.

Abstract: A method is disclosed for processing data stream within a time constraint by a stream processing network having a plurality of processing elements. The method includes determining a processing unit, by selecting at least one of the plurality of processing elements, for transmitting next data items of the data stream; collecting system information of the processing unit, wherein the system information includes load information of the selected processing element; adapting, based on the system information, a sending rate of the data stream; discarding, by the processing unit, data items of the data stream that would not be processed within the time constraint; and sending, by the processing unit, data items of the data stream that would be processed within the time constraint.