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The continuous growth of the Internet of Things together with the complexity of modern information systems results in several challenges for modeling, provisioning, executing, and maintaining systems that are capable of adapting themselves to changing situations in dynamic environments. The properties of the workflow technology, such as its recovery features, makes this technology suitable to be leveraged in such environments. However, the realization of situation-aware mechanisms that dynamically adapt process executions to changing situations is not trivial and error prone, since workflow modelers cannot reflect all possibly occurring situations in complex environments in their workflow models. In this paper, we present a method and concepts to enable modelers to create traditional, situation-independent workflow models that are automatically transformed into situation-aware workflow models that cope with dynamic contextual situations. Our work builds upon the usage of workflow fragments, which are dynamically selected during runtime to cope with prevailing situations retrieved from low-level context sensor data. We validate the practical feasibility of our work by a prototypical implementation of a Situation-aware Workflow Management System (SaWMS) that supports the presented concepts.

Abstract. The Internet of Things benefits from an increasing number of interconnected technical devices. This has led to the existence of so-called smart environments, which encompass one or more devices sensing, acting, and automatically performing different tasks to enable their self-organization. Smart environments are divided into two parts: the physical environment and its digital representation, oftentimes referred to as digital twin. However, the automated binding and monitoring of devices of smart environments are still major issues. In this article we present a method and system architecture to cope with these challenges by enabling (i) easy modeling of sensors, actuators, devices, and their attributes, (ii) dynamic device binding based on their type, (iii) the access to devices using different paradigms, and (iv) the monitoring of smart environments in regard to failures or changes. We furthermore provide a prototypical implementation of the introduced approach.

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