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Example of a system with 5 partitions and different criticality levels. (a) architecture and (b) CPU allocation.
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Embedded systems used in critical systems, such as aeronautics, have undergone continuous evolution in recent years. In this evolution, many of the functionalities offered by these systems have been adapted through the introduction of network services that achieve high levels of interconnectivity. The high availability of access to communications n...
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Advances in Artificial intelligence (AI) and embedded systems have resulted on a recent increase in use of image processing applications for smart cities’ safety. This enables a cost-adequate scale of automated video surveillance, increasing the data available and releasing human intervention. At the same time, although deep learning is a very inte...
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... Entrepreneurs, in order to be competitive, must monitor and reliably receive stimuli and signals from the environment, use them, implement innovative solutions in their products, and improve the functioning of the enterprise by optimising processes and management systems. The knowledge-based economy is becoming apparent, the importance of resources at the disposal of the company is changing, and intangible capital is beginning to dominate among the resources of manufacturing enterprises [16,22]. ...
The foundry industry consumes significant amounts of natural resources, metals, and energy, and it generates large amounts of solid waste and gases, which have a significant impact on the environment. Therefore, taking sustainability-based improvement measures in foundry companies is necessary and an important part of sustainable development for humanity. The aim of this study was to develop a universal indicator model for quality control improvement focused on the foundry industry. The model allows a multi-criteria analysis of various quality control methods and the determination of their gradation in the context of ensuring an objectively high level of product quality. A test of the model carried out in foundry companies confirmed its suitability. An optimisation of the relationship between product quality and quality control efficiency was carried out, which fulfilled the criteria of efficiency, reliability, low emissivity, low energy intensity, low cost, short lead time, and automation. Thanks to the indicated features, the model clearly fits into the concept of sustainable development and Industry 4.0. The result of the realised research, i.e., the ranking of the gradation of detection methods, allowed optimisation of quality control within the analysed production process. Future research directions will address the integration of digital solutions within the model.
... Al igual que la industria automovilística, los sistemas embebidos siguen avanzando constantemente, enfocados actualmente en requisitos de SWaP (Size, Weight and Power), con el fin de proporcionar sistemas más pequeños, ligeros y con un menor consumo energético, a la vez que se incrementa la capacidad de procesamiento. Estos CPSs (Simó et al., 2021) se ven claramente beneficiados del uso de los nuevos procesadores multicore, que permiten incorporar nuevas tecnologías como pueden ser los sistemas particionados y las características de tiempo real. Esto es realmente conveniente, ya que tanto las nuevas exigencias legislativas, como las recientes innovaciones incorporadas en los vehículos, hace que se requieran sistemas de mayor potencia. ...
Este artículo presenta el diseño de una arquitectura particionada de criticidad mixta aplicada a un prototipo de vehículo autónomo en el contexto del transporte público. La movilidad inteligente, sostenible y segura es una meta aún no alcanzada, por ello este artículo propone una solución basada en un sistema ciberfísico (CPS). El CPS emula las capacidades del vehículo autónomo, incluyendo la recopilación de datos del entorno, su procesamiento en tiempo real y la toma de decisiones y de acciones mediante los actuadores de este. El principal problema que se presenta en sistemas mixtos son las posibles interferencias causadas por los diferentes niveles de criticidad de las tareas. Se propone como solución el uso del particionado, buscando aprovechar el rendimiento del multiprocesador, aumentar la seguridad y reducir costes en el proceso.
... TT traffic can be combined with best-effort traffic and audio-video bridging (AVB) traffic or rate constrained (RC) traffic and form a hybrid critical network. In a time-triggered (TT) network, TT traffic is set as the highest priority traffic and is designed off-line [4][5][6]. This implies that it is scheduled in advance and then loaded onto each node to ensure that its transmission (a) does not suffer from blocking delays due to transmission conflicts between TT traffic, and (b) is not affected by other low priority traffic in the network [7,8]. ...
... For example, if p A = 8, p B = 12 and l A = l B = 1, thus lcm = 24 and gcd = 4. When the time-slots occupied by TT flow A are predetermined to be [1,9,17], there are gcd−1 gcd × p B = 4−1 4 × 12 = 9 number of scenarios in which TT flow B can be scheduled, namely [2,14], [3,15], [4,16], [6,18], [7,19], [8,20], [10,22], [11,23], [12,24]. ...
... × 12 = 3 number of scenarios in which TT flow B can be scheduled, namely [2,3,4,14,15,16], [6,7,8,18,19,20], [10,11,12,22,23,24]. ...
Time-triggered networks are deployed in avionics and astronautics because they provide deterministic and low-latency communications. Remapping of partitions and the applications that reside in them that are executing on the failed core and the resulting re-routing and re-scheduling are conducted when a permanent end-system core failure occurs and local resources are insufficient. We present a network-wide reconfiguration strategy as well as an implementation scheme, and propose an Integer Linear Programming based joint mapping, routing, and scheduling reconfiguration method (JILP) for global reconfiguration. Based on scheduling compatibility, a novel heuristic algorithm (SCA) for mapping and routing is proposed to reduce the reconfiguration time. Experimentally, JILP achieved a higher success rate compared to mapping-then-routing-and-scheduling algorithms. In addition, relative to JILP, SCA/ILP was 50-fold faster and with a minimal impact on reconfiguration success rate. SCA achieved a higher reconfiguration success rate compared to shortest path routing and load-balanced routing. In addition, scheduling compatibility plays a guiding role in ILP-based optimization objectives and ‘reconfigurable depth’, which is a metric proposed in this paper for the determination of the reconfiguration potential of a TT network.
... Indeed, the system begins its operation with 1 mode, and it enters into 2 mode whenever an 2 overruns its 1 . Now, the scheduler assumes 2 for all the residual workloads to ensure the system correctness, and it continues in this mode until all the high-level workloads are completed; now, the operation of all 1 and 2 tasks demands heavy computation, which may surpass the system's capacity, and the processor becomes overloaded [8]. ...
Recently, scheduling mixed-criticality tasks on a common computational system has become an imperative study in academia and engineering proposals. Since multicore processors are the main paradigm in mixed-criticality systems (MCS), reliability and energy consumption are vital concerns. In modern MCS, increased peak power dissipation, particularly in critical scenarios, may cause temperature issues, disturbing the system's consistency and timeliness. This work proposes a criticality-cognizant energy-efficient scheduling approach (CESA) that concurrently provides reliability, power management, and failsafe service level in MCS. The proposed approach decreases the system power dissipation as far as achievable at runtime through the dynamic voltage and frequency scaling (DVFS) approach with laxity allocation. CESA simultaneously accepts a number of tasks (i.e., workloads) and creates clusters with one high-criticality workload and a set of low-criticality workloads. It calculates the available laxities effectively and finds the most suitable task cluster to utilize that available laxity by considering its effect on the instantaneous power consumption and thermal issues. At the same time, varying the core speed, assigning an appropriate cluster for remaining laxity, and selecting a suitable core for task migration at runtime are arduous endeavors and lead to deadline defilement which is not acceptable for high-level workloads. Hence, we propose an online scheduling approach with DVFS and task migration during runtime whenever there is laxity. A cost function is defined as finding out the most suitable cluster to allot the laxities to reduce its V/F level or transfer the task to a new processing element. We assess the performance of our approach in an asymmetric multicore platform (i.e., ARM big. LITTLE processor) with several benchmark task sets. Empirical results demonstrate that the proposed algorithm realizes up to a 6.76% drop in maximum power and a 26.17% drop in core temperature related to the state-of-the-art method.
... The evolution of the industrial component model for multi-criticality vehicular software is addressed by Bucaioni et al. [123]. In a wider context, Simo et al. [564] discuss the role of MCS within the context of Industry 4.0. An analysis of task parameters for automotive application is presented by Nair et al. [473]. ...
This review covers research on the topic of mixed criticality systems that has been published since Vestal’s 2007 paper. It covers the period up to end of 2021. The review is organised into the following topics: introduction and motivation, models, single processor analysis (including job-based, hard and soft tasks, fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, related topics, realistic models, formal treatments, systems issues, industrial practice and research beyond mixed-criticality. A list of PhDs awarded for research relating to mixed-criticality systems is also included.
... For example, in an aeroplane, the correct operation of the engines is of higher criticality than the onboard intercom system. With the seminal work by Vestal in 2007 [1], scheduling of mixed-criticality systems became an active research field [2][3][4][5][6][7][8]. ...
... PFD PFH 4 10 −4 to 10 −5 10 −8 to 10 −9 3 10 −3 to 10 −4 10 −7 to 10 −8 2 10 −2 to 10 −3 10 −6 to 10 −7 1 10 −1 to 10 −2 10 −5 to 10 −6 ...
Many safety-critical systems use criticality arithmetic, an informal practice of implementing a higher-criticality function by combining several lower-criticality redundant components or tasks. This lowers the cost of development, but existing mixed-criticality schedulers may act incorrectly as they lack the knowledge that the lower-criticality tasks are operating together to implement a single higher-criticality function. In this paper, we propose a solution to this problem by presenting a mixed-criticality mid-term scheduler that considers where criticality arithmetic is used in the system. As this scheduler, which we term ATMP-CA, is a mid-term scheduler, it changes the configuration of the system when needed based on the recent history of deadline misses. We present the results from a series of experiments that show that ATMP-CA’s operation provides a smoother degradation of service compared with reference schedulers that do not consider the use of criticality arithmetic.
With the development of the Internet of Things and distributed systems, both the applications and the hardware support increased their complexity. This evolution resulted in an inevitable move toward multicore platforms at the edge of the Internet of Things in real-time and safety-critical systems. This shift to multicore architectures reflects also in the transformation and evolution of the mixed-criticality real-time task scheduling techniques, which still face several challenges due to their restricted resources and safety-critical aspects that include determinism, predictability, task isolation, resource management and low power consumption. The goal of this chapter is to present a survey on the state of the art multicore scheduling techniques, with a focus on task-allocation algorithms for mixed-criticality real-time systems, while identifying the research gaps and future trends.
