Designing a Framework for Smart IoT Adaptations

International audienceThe Internet of Things (IoT) is the science of connecting multiple devices that coordinate to provide the service in question. IoT environments are complex, dynamic, rapidly changing and resource constrained. Therefore, proactively adapting devices to align with context fluctuations becomes a concern. To propose suitable configurations, it should be possible to sense information from devices, analyze the data and reconfigure them accordingly. Applied in the service of the environment, a fleet of devices can monitor environment indicators and control it in order to propose best fit solutions or prevent risks like over consumption of resources (e.g., water and energy). This paper describes our methodology in designing a framework for the monitoring and multi-instantiation of fleets of connected objects. First by identifying the particularities of the fleet, then by specifying connected object as a Dynamic Software Product Line (DSPL), capable of readjusting while running

Development of a Modeling Architecture Incorporating the Industry 4.0 View for a Company in the Gas Sector

Part 7: Cyber-Physical SystemsInternational audienceIndustry 4.0 is a fast growing concept which has started to gain ground over the last few years and strives to achieve a higher and more efficient production rate through the usage of automations. This concept is directly correlated with Business Process Management because its implementation concerns the improvement of business processes. Business Process Modeling is a tool of Business Process Management which can depict the processes of an organization in order to be elaborated and improved. For that reason models are widely used for the better understanding of processes and as a first step of new concepts insertion, such as Industry 4.0, in an organization. Hence, a comprehensive framework of a modeling architecture is essential for a company which desires the transition to new concepts according to its needs, its processes and its structure. In this paper, a complete architecture which proposed in a company activating in gas industry is presented including the appropriate models for the recording of business processes and how Industry 4.0 principles could be incorporated to them

Hierarchical performance analysis for process mining

Process mining techniques use event data from operational and software processes to discover process models, to check the conformance of predefined process models, and to extend such models with information about bottlenecks, decisions, and resource usage. In recent years, the process mining field made huge advances in terms of scalability. In addition, recent work in process discovery supports advanced process model constructs such as subprocesses, recursive structures, cancellation, and various notions of concurrency. Hence, one has to realize that a simple, small, and flat model will not suffice anymore, especially when applied to analyzing software system processes. However, state of the art performance analysis is still typically performed either over the whole process model or at the level of individual activities. There is a lack of formal support for performance analysis on various submodel abstractions while taking into account the execution semantics. This paper presents 1) a framework for establishing precise relationships between events and submodels, taking into account execution semantics; and 2) a novel formalization of existing and novel performance metrics. Our approach enables advanced performance analysis at various submodel abstractions. An implementation is made available, and we demonstrate the advantages of our approach to various software system processes, showing the applicability and advantage with respect to existing techniques