Enabling Self-adaptive Workflows for Cyber-physical Systems


The ongoing development of Internet of Things technologies leads to the interweaving of the virtual world of software with the physical world. However, applying workflow technologies for automating processes in these Cyber-physical Systems (CPS) poses new challenges as the real world effects of a process have to be verified to provide a consistent view of the cyber and physical world executions. In this work we present a synchronization and adaptation mechanism for processes based on the MAPE-K feedback loop for self-adaptive systems. By applying this loop, sensor and context information can be used to verify the real world effects of workflow execution and adapt the process in case of errors. The approach increases autonomy and resilience of process execution in CPS due to the self-adaptation capabilities. We present generic extensions to process meta-models and execution engines to implement the feedback loop and discuss our approach within a smart home scenario.

In Enterprise, Business-Process and Information Systems Modeling (BPMDS 2016), Lecture Notes in Business Information Processing, vol 248. Springer, Cham