Micro-workflows: Kafka and kepler fusion to support digital twins of industrial processes

In recent years, we observe an exponential growth of 'Smart Industry' concept that relies on the use of software and hardware systems to analyze data from several types of smart sensors by various types of models: mathematical, computational, data, etc. A set of such virtual models, representing processes, systems and equipment is called 'Digital Twins' (DTs). DTs use data gathered from the sensory systems on production lines to predict failures of machinery, optimize the quality of the products, and reduce the ecological footprint from facilities. They can be described as a sequence of jobs that perform required functionality linked together by a set of edges that represent data dependencies. To organize a flexible cloud computing support for the Digital Twin execution, we propose a concept of Micro-Workflows that combines the power of scientific workflows, the flexibility of containers technology, and robustness of the distributed streaming approach. © 2018 IEEE.