| 1. |
- Törngren, Martin, et al.
(författare)
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A modelling framework to support the design and analysis of distributed real-time control systems
- 2000
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Ingår i: Microprocessors and microsystems. - 0141-9331 .- 1872-9436. ; 24:2, s. 81-93
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Tidskriftsartikel (refereegranskat)abstract
- Within the automatic control in distributed applications project a modelling framework has been developed to support design issues related to the implementation of control applications in embedded distributed computer systems. At a relatively high level of abstraction the models describe the structure and timing behaviour of a control application (in terms of functions and operational models) and its implementation (hardware, operating system threads and resources). The resource description allows the timing behaviour of the implementation to be analysed and fed back into the application models. The models form the basis for a decentralization tool-set, where a first prototype is under development. Examples of the models are given and the framework is compared to related modelling approaches.
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| 2. |
- Afzal, Wasif, et al.
(författare)
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The MegaM@Rt2 ECSEL project : MegaModelling at Runtime – Scalable model-based framework for continuous development and runtime validation of complex systems
- 2018
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Ingår i: Microprocessors and microsystems. - : Elsevier B.V.. - 0141-9331 .- 1872-9436. ; 61, s. 86-95
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Tidskriftsartikel (refereegranskat)abstract
- A major challenge for the European electronic industry is to enhance productivity by ensuring quality of development, integration and maintenance while reducing the associated costs. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities, but they still need to scale up to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration, and communication between two fundamental system life cycle phases (design time and runtime) is another challenge requiring the scalability of MDE. This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design and continuous development, 2) related runtime analysis and 3) global models and traceability management. Diverse industrial use cases (covering strategic domains such as aeronautics, railway, construction and telecommunications) will integrate and demonstrate the validity of the MegaM@Rt2 solution. This paper provides an overview of the MegaM@Rt2 project with respect to its approach, mission, objectives as well as to its implementation details. It further introduces the consortium as well as describes the work packages and few already produced deliverables.
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| 3. |
- Agirre, J. A., et al.
(författare)
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The VALU3S ECSEL project : Verification and validation of automated systems safety and security
- 2021
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Ingår i: Microprocessors and microsystems. - : Elsevier BV. - 0141-9331 .- 1872-9436. ; 87, s. 104349-
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Tidskriftsartikel (refereegranskat)abstract
- Manufacturers of automated systems and their components have been allocating an enormous amount of time and effort in R&D activities, which led to the availability of prototypes demonstrating new capabilities as well as the introduction of such systems to the market within different domains. Manufacturers need to make sure that the systems function in the intended way and according to specifications. This is not a trivial task as system complexity rises dramatically the more integrated and interconnected these systems become with the addition of automated functionality and features to them. This effort translates into an overhead on the V&V (verification and validation) process making it time-consuming and costly. In this paper, we present VALU3S, an ECSEL JU (joint undertaking) project that aims to evaluate the state-of-the-art V&V methods and tools, and design a multi-domain framework to create a clear structure around the components and elements needed to conduct the V&V process. The main expected benefit of the framework is to reduce time and cost needed to verify and validate automated systems with respect to safety, cyber-security, and privacy requirements. This is done through identification and classification of evaluation methods, tools, environments and concepts for V&V of automated systems with respect to the mentioned requirements. VALU3S will provide guidelines to the V&V community including engineers and researchers on how the V&V of automated systems could be improved considering the cost, time and effort of conducting V&V processes. To this end, VALU3S brings together a consortium with partners from 10 different countries, amounting to a mix of 25 industrial partners, 6 leading research institutes, and 10 universities to reach the project goal.
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| 4. |
- Asghari, S. A., et al.
(författare)
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A software implemented comprehensive soft error detection method for embedded systems
- 2020
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Ingår i: Microprocessors and microsystems. - : Elsevier. - 0141-9331 .- 1872-9436. ; 77
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a comprehensive software-based technique that is capable of detecting soft errors in embedded systems. Soft errors can be categorized into Control Flow Errors (CFEs) and data errors. The CFEs change the flow of the program erroneously and data errors also change the results. In this paper, a new comprehensive method is presented to detect both (based on combination of authors’ previous works). In order to evaluate the proposed method, a new factor is defined that considers three main parameters simultaneously; namely fault coverage, memory overhead, and performance overhead. Since these parameters are very important in safety critical applications, they should be improved concurrently. The experimental results on SPEC2000 benchmarks show that the Evaluation Factor of the proposed method is 50% better than the Relationship Signatures for Control Flow Checking with Data Validation (RSCFCDV) methods, which are suggested in the literature.
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| 5. |
- Badawi, Mohammad, et al.
(författare)
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Quality-of-service-aware adaptation scheme for multi-core protocol processing architecture
- 2017
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Ingår i: Microprocessors and microsystems. - : Elsevier. - 0141-9331 .- 1872-9436. ; 54, s. 47-59
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Tidskriftsartikel (refereegranskat)abstract
- Employing adaptable protocol processing architectures has shown a high potential in provisioning Quality-of-Service (QoS) while retaining efficient use of available energy budget. Nevertheless, successful QoS provisioning using adaptable protocol processing architectures requires adaption to be agile and to have low latency. That is, a long adaptation latency might lead to violating desired packet processing latency, desired throughput or loss of packets if the memory fails to accommodate packet accumulation. This paper presents an elastic management scheme to permit agile and QoS-aware adaptation of processing elements (PEs) within the protocol processing architecture, such that desired QoS is maintained. Moreover, our proposed scheme has the potential to reduce energy consumption since it employs the PEs upon demand. We quantify the latency required for PEs adaptation, the reduction in energy and the reduction in area that can be achieved using our scheme. We also consider two different real-life use cases to demonstrate the effectiveness of our proposed management scheme in maintaining QoS while conserving available energy.
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| 6. |
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| 7. |
- Bruneliere, H., et al.
(författare)
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AIDOaRt : AI-augmented Automation for DevOps, a model-based framework for continuous development in Cyber–Physical Systems
- 2022
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Ingår i: Microprocessors and microsystems. - : Elsevier B.V.. - 0141-9331 .- 1872-9436. ; 94
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Tidskriftsartikel (refereegranskat)abstract
- The advent of complex Cyber–Physical Systems (CPSs) creates the need for more efficient engineering processes. Recently, DevOps promoted the idea of considering a closer continuous integration between system development (including its design) and operational deployment. Despite their use being still currently limited, Artificial Intelligence (AI) techniques are suitable candidates for improving such system engineering activities (cf. AIOps). In this context, AIDOaRT is a large European collaborative project that aims at providing AI-augmented automation capabilities to better support the modeling, coding, testing, monitoring, and continuous development of CPSs. The project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable CPSs. The resulting framework will (1) enable the dynamic observation and analysis of system data collected at both runtime and design time and (2) provide dedicated AI-augmented solutions that will then be validated in concrete industrial cases. This paper describes the main research objectives and underlying paradigms of the AIDOaRt project. It also introduces the conceptual architecture and proposed approach of the AIDOaRt overall solution. Finally, it reports on the actual project practices and discusses the current results and future plans.
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| 8. |
- Castillejo, Pedro, et al.
(författare)
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Aggregate Farming in the Cloud : The AFarCloud ECSEL project
- 2020
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Ingår i: Microprocessors and microsystems. - : Elsevier B.V.. - 0141-9331 .- 1872-9436. ; 78
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Tidskriftsartikel (refereegranskat)abstract
- Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate monitoring of soil and crop properties and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate Farming in the Cloud) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labor costs. Moreover, such a platform can be integrated with farm management software to support monitoring and decision-making solutions based on big data and real-time data mining techniques. © 2020 The Author(s)
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| 9. |
- Chen, Kun-Chih (jimmy), et al.
(författare)
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A NoC-based simulator for design and evaluation of deep neural networks
- 2020
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Ingår i: Microprocessors and microsystems. - : ELSEVIER. - 0141-9331 .- 1872-9436. ; 77
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Tidskriftsartikel (refereegranskat)abstract
- The astonishing development in the field of artificial neural networks (ANN) has brought significant advancement in many application domains, such as pattern recognition, image classification, and computer vision. ANN imitates neuron behaviors and makes a decision or prediction by learning patterns and features from the given data set. To reach higher accuracies, neural networks are getting deeper, and consequently, the computation and storage demands on hardware platforms are steadily increasing. In addition, the massive data communication among neurons makes the interconnection more complex and challenging. To overcome these challenges, ASIC-based DNN accelerators are being designed which usually incorporate customized processing elements, fixed interconnection, and large off-chip memory storage. As a result, DNN computation involves large memory accesses due to frequent load/off-loading data, which significantly increases the energy consumption and latency. Also, the rigid architecture and interconnection among processing elements limit the efficiency of the platform to specific applications. In recent years, Network-on-Chip-based (NoC-based) DNN becomes an emerging design paradigm because the NoC interconnection can help to reduce the off-chip memory accesses while offers better scalability and flexibility. To evaluate the NoC-based DNN in the early design stage, we introduce a cycle-accurate NoC-based DNN simulator, called DNNoC-sim. To support various operations such as convolution and pooling in the modern DNN models, we first propose a DNN flattening technique to convert diverse DNN operation into MAC-like operations. In addition, we propose a DNN slicing method to evaluate the large-scale DNN models on a resource-constraint NoC platform. The evaluation results show a significant reduction in the off-chip memory accesses compared to the state-of-the-art DNN model. We also analyze the performance and discuss the trade-off between different design parameters.
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| 10. |
- Daneshtalab, Masoud, et al.
(författare)
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Special issue on many-core embedded systems
- 2014
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Ingår i: Microprocessors and microsystems. - : Elsevier BV. - 0141-9331 .- 1872-9436. ; 38:6, s. 525-525
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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