The Internet of Things (IoT) and Industrial Internet of Things (IIoT) trends, where high connectivity is envisioned, are giving rise to new applications, services, and paradigms, such as smart cities. Due to this connectivity and information sharing features, security, and privacy protection mechanisms need to be implemented, which may become obsolete at some future time. Software updates are, then, crucial. However, software updates requiring system shutdown and restarts might not be acceptable from the business and service point of view when high availability is demanded. In this paper, a mixed-criticality software architecture and design for a building energy management system, built upon the Cetratus runtime framework, is presented, where partitioning techniques are employed to ensure temporal and spatial isolation. Through this framework, software updates are dynamically accomplished, without the need for system shutdown and restarts. A live patching example is also presented, where customers privacy is enhanced by means of homomorphic encryption.

Modern industrial cyberphisical systems exhibit increasingly complex execution patterns like multipath endto-end flows, that force the real-time community to extend the schedulability analysis methods to include these patterns. Only then it is possible to ensure that applications meet their deadlines even in the worstcase scenario. As a driving motivation, we present a real industrial application with safety requirements, that needs to be re-factored in order to leverage the features of new execution paradigms such as time partitioning. In this context we develop a new response-time analysis technique that provides the capacity of obtaining the worst-case response time of multipath flows in time-partitioned hierarchical schedulers and also in general fixed-priority (FP) real-time systems. We show that the results obtained with the new analysis reduce the pessimism of the currently used holistic analysis approach. INDEX TERMS Schedulability analysis, time partitioning, hierarchical scheduling, distributed systems, safety, industrial application.

<p>En las últimas tres décadas, se ha realizado un gran número de propuestas sobre la optimización del despliegue y planificación de sistemas de tiempo real distribuidos bajo diferentes enfoques algorítmicos que aportan soluciones aceptables a este problema catalogado como NP-difícil. En la actualidad, la mayor parte de los sistemas utilizados en el sector industrial son sistemas de criticidad mixta en los que se puede usar la planificación cíclica, las prioridades fijas y el particionado, que proporciona aislamiento temporal y espacial a las aplicaciones. Así, en este artículo se realiza una revisión de los trabajos publicados sobre este tema y se presenta un análisis de las diferentes soluciones aportadas para sistemas de tiempo real distribuidos basados en las políticas de<br />planificación que se están usando en la práctica. Como resultado de la comparación, se presenta una tabla a modo de guía en la que se relacionan los trabajos revisados y se caracterizan sus soluciones.</p>

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