Critical and distributed systems need to be reliable and comply with the required performance at run-time. In this vein, data distribution service for real-time systems (DDS) provides developers with highly configurable middleware to control the end-to-end quality of service (QoS) of the applications through a wide range of attributes. However, dynamic and unpredictable environment pose a major challenge to these systems as their workload and resources may fluctuate significantly in time depending on the execution context. Developers usually find it difficult to choose and apply the right DDS QoS attributes, as once selected, they remain fixed during the whole execution of the system. They do not automatically change according to the execution context, e.g., to meet nonfunctional requirements related to performance or resource consumption. Moreover, changing the QoS attributes at run-time may lead to incompatibilities, since the configuration used by the different participants needs to be mutually consistent. In this paper, we propose a model-driven approach that enables the safe, automatic, and transparent adaptation of the QoS attributes in DDS-based middleware, providing the best performance possible within the available resources at run-time. An example in robotics is presented to demonstrate the feasibility and the benefits of our proposal.

Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate frail elderly people in order to create therapy plans that improve their quality and quantity of life. The whole process includes the completion of standardized questionnaires or specific movements, which are performed by the patient and do not necessarily require the presence of a medical expert. With the aim of automatizing these parts of the CGA, we have designed and developed CLARC (smart CLinic Assistant Robot for CGA), a mobile robot able to help the physician to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined evaluation tests. Using CLARC to conduct geriatric tests will reduce the time medical professionals have to spend on purely mechanical tasks, giving them more time to develop individualised care plans for their patients. In fact, ideally, CLARC will perform these tests on its own. In parallel with the effort to correctly address the functional aspects, i.e., the development of the robot tasks, the design of CLARC must also deal with non-functional properties such as the degree of interaction or the performance. We argue that satisfying user preferences can be a good way to improve the acceptance of the robot by the patients. This paper describes the integration into the software architecture of the CLARC robot of the modules that allow these properties to be monitored at run-time, providing information on the quality of its service. Experimental evaluation illustrates that the defined quality of service metrics correctly capture the evolution of the aspects of the robot’s activity and its interaction with the patient covered by the non-functional properties that have been considered.

This article introduces a blueprint architecture for long collaboration chains formed by systems of systems, provided by multiple companies, that can significantly improve the understanding of the processes and events taking place. We illustrate the vision with an automated supply chain scenario and utilize example use cases.