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| 2. |
- Bucaioni, Alessio, 1987-, et al.
(författare)
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MoVES : a Model-driven methodology for Vehicular Embedded Systems
- 2018
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Ingår i: IEEE Access. - 2169-3536. ; , s. 6424-6445
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Tidskriftsartikel (refereegranskat)abstract
- This paper introduces a novel model-driven methodology for the software development of real-time distributed vehicular embedded systems on single- and multi-core platforms. The proposed methodology discloses the opportunity of improving the cost-efficiency of the development process by providing automated support to identify viable design solutions with respect to selected non-functional requirements. To this end, it leverages the interplay of modelling languages for the vehicular domain whose integration is achieved by a suite of model transformations. An instantiation of the methodology is discussed for timing requirements, which are among the most critical ones for vehicular systems. To support the design of temporally correct systems, a cooperation between EAST-ADL and the Rubus Component Model is opportunely built-up by means of model transformations, enabling timing-aware design and model-based timing analysis of the system. The applicability of the methodology is demonstrated as proof of concepts on industrial use cases performed in cooperation with our industrial partners.
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| 3. |
- Danielsson, Jakob, et al.
(författare)
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Resource Depedency Analysis in Multi-Core Systems
- 2020
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Ingår i: Proceedings - 2020 IEEE 44th Annual Computers, Software, and Applications Conference, COMPSAC 2020. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728173030 ; , s. 87-94
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Konferensbidrag (refereegranskat)abstract
- In this paper, we evaluate different methods for statistical determination of application resource dependency in multi-core systems. We measure the performance counters of an application during run-time and create a system resource usage profile. We then use the resource profile to evaluate the application dependency on the specific resource. We discuss and evaluate two methods to process the data, including moving average filter and partitioning the data into smaller segments in order to interpret data for correlation calculations. Our aim with this study is to evaluate and create a generalizeable methods for automatic determination of resource dependencies. The final outcome of the methods used in this study is the answer to the question: 'To what resources is this application dependent on?'. The recommendation of this tool will be used in conjunction with our last-level cache partitioning controller (LLC-PC), to make decision if an application should receive last-level cache partition slices.
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| 4. |
- Hansson, Hans, et al.
(författare)
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Real-time in embedded systems
- 2017
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Ingår i: Systems, Controls, Embedded Systems, Energy, and Machines. - : CRC Press. - 9781420037043 - 0849373476 - 9780849373473 ; , s. 16-26-16-58
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 5. |
- Loni, Mohammad, et al.
(författare)
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AutoRIO: An Indoor Testbed for Developing Autonomous Vehicles
- 2018
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Ingår i: International Japan-Africa Conference on Electronics, Communications and Computations JAC-ECC. - 9781538692301 ; , s. 69-72
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Konferensbidrag (refereegranskat)abstract
- Autonomous vehicles have a great influence on our life. These vehicles are more convenient, more energy efficient providing higher safety level and cheaper driving solutions. In addition, decreasing the generation of CO 2 , and the risk vehicular accidents are other benefits of autonomous vehicles. However, leveraging a full autonomous system is challenging and the proposed solutions are newfound. Providing a testbed for evaluating new algorithms is beneficial for researchers and hardware developers to verify the real impact of their solutions. The existence of testing environment is a low-cost infrastructure leading to increase the time-to-market of novel ideas. In this paper, we propose Auto Rio, a cutting-edge indoor testbed for developing autonomous vehicles.
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| 6. |
- Loni, Mohammad, et al.
(författare)
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Designing compact convolutional neural network for embedded stereo vision systems
- 2018
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Ingår i: Proceedings - 2018 IEEE 12th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2018. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538666890 ; , s. 244-251
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Konferensbidrag (refereegranskat)abstract
- Autonomous systems are used in a wide range of domains from indoor utensils to autonomous robot surgeries and self-driving cars. Stereo vision cameras probably are the most flexible sensing way in these systems since they can extract depth, luminance, color, and shape information. However, stereo vision based applications suffer from huge image sizes and computational complexity leading system to higher power consumption. To tackle these challenges, in the first step, GIMME2 stereo vision system [1] is employed. GIMME2 is a high-throughput and cost efficient FPGA-based stereo vision embedded system. In the next step, we present a framework for designing an optimized Deep Convolutional Neural Network (DCNN) for time constraint applications and/or limited resource budget platforms. Our framework tries to automatically generate a highly robust DCNN architecture for image data receiving from stereo vision cameras. Our proposed framework takes advantage of a multi-objective evolutionary optimization approach to design a near-optimal network architecture for both the accuracy and network size objectives. Unlike recent works aiming to generate a highly accurate network, we also considered the network size parameters to build a highly compact architecture. After designing a robust network, our proposed framework maps generated network on a multi/many core heterogeneous System-on-Chip (SoC). In addition, we have integrated our framework to the GIMME2 processing pipeline such that it can also estimate the distance of detected objects. The generated network by our framework offers up to 24x compression rate while losing only 5% accuracy compare to the best result on the CIFAR-10 dataset.
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| 7. |
- Loni, Mohammad, et al.
(författare)
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NeuroPower : Designing Energy Efficient Convolutional Neural Network Architecture for Embedded Systems
- 2019
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Ingår i: Lecture Notes in Computer Science, Volume 11727. - Munich, Germany : Springer. - 9783030304867 ; 11727 LNCS, s. 208-222
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Konferensbidrag (refereegranskat)abstract
- Convolutional Neural Networks (CNNs) suffer from energy-hungry implementation due to their computation and memory intensive processing patterns. This problem is even more significant by the proliferation of CNNs on embedded platforms. To overcome this problem, we offer NeuroPower as an automatic framework that designs a highly optimized and energy efficient set of CNN architectures for embedded systems. NeuroPower explores and prunes the design space to find improved set of neural architectures. Toward this aim, a multi-objective optimization strategy is integrated to solve Neural Architecture Search (NAS) problem by near-optimal tuning network hyperparameters. The main objectives of the optimization algorithm are network accuracy and number of parameters in the network. The evaluation results show the effectiveness of NeuroPower on energy consumption, compacting rate and inference time compared to other cutting-edge approaches. In comparison with the best results on CIFAR-10/CIFAR-100 datasets, a generated network by NeuroPower presents up to 2.1x/1.56x compression rate, 1.59x/3.46x speedup and 1.52x/1.82x power saving while loses 2.4%/-0.6% accuracy, respectively.
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| 8. |
- Martin, G., et al.
(författare)
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Embedded systems - An Overview
- 2017
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Ingår i: Systems, Controls, Embedded Systems, Energy, and Machines. - Boca Raton : CRC Press. - 9781420037043 - 0849373476 - 9780849373473 ; , s. 16-1-16-1
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Embedded systems span a number of scienti?c and engineering disciplines, which evolve continuously. So does the ?eld of embedded systems. To write on this topic requires a careful choice of the material to be covered, to make a presentation of a reasonable length, and provide a fairly up-to-date material. This chapter focuses on two main areas of embedded systems, which have evolved only in recent years, namely, systems on a chip and networked embedded systems. The section on System-on-Chip surveys a large number of the issues involved in its design. The section on networked embedded systems presents an overview of trends for networking of embedded systems, their design, and their application for in-car controls and automation. This material is preceded by a round up of embedded systems in general, and design trends.
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| 9. |
- Mubeen, Saad, et al.
(författare)
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Holistic modeling of time sensitive networking in component-based vehicular embedded systems
- 2019
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Ingår i: Euromicro Conference on Software Engineering and Advanced Applications SEAA 2019. - : Institute of Electrical and Electronics Engineers Inc.. ; , s. 131-139
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Konferensbidrag (refereegranskat)abstract
- This paper presents the first holistic modeling approach for Time-Sensitive Networking (TSN) communication that integrates into a model- and component-based software development framework for distributed embedded systems. Based on these new models, we also present an end-to-end timing model for TSN-interconnected distributed embedded systems. Our approach is expressive enough to model the timing information of TSN and the timing behaviour of software that communicates over TSN, hence allowing end-to-end timing analysis. A proof of concept for the proposed approach is provided by implementing it for a component model and tool suite used in the vehicle industry. Moreover, a use case from the vehicle industry is modeled and analyzed with the proposed approach to demonstrate its usability.
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| 10. |
- Neander, Jonas, 1971-
(författare)
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Using Existing Infrastructure as Support for Wireless Sensor Networks
- 2006
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Denna avhandling handlar om hur befintliga datorinfrastrukturer i t.ex. sjukhus och industrier kan avlasta sensornätverk med energikrävande uppgifter. Vi har forskat på olika aspekter som gör det möjligt att förlänga livslängden på dessa sensornätverk. Avhandlingen presenterar en ny plattform för sensornätverk tillsammans med inledande simuleringar som påvisar att vår plattform ökar livslängden på dessa typer av nätverk.Generella sensornätverk är uppbyggda av tätt grupperade, trådlösa, batteridrivna datorer som kan vara så små som en kubikmillimeter. Datorerna kallas för sensorer eller sensornoder eftersom de har en eller flera inbyggda sensorer som känner av sin omgivning. En sensor har till uppgift att samla information från sin omgivning, t.ex. temperatur, fuktighet, vibrationer, hjärtslag eller bilder. Sensorerna skickar sedan informationen till en insamlingsstation någonstans i nätverket.I de typer av tillämpningar vi tittar på är det viktigt att minimera energiförbrukningen, så att man maximerar livslängden på sensornätverket. Avhandlingen presenterar en lösning där befintlig datorinfrastruktur fungerar som hjälpdatorer/avlastare till ett sensornätverk. Hjälpdatorerna, eller basstationerna som vi kallar dem i avhandlingen, hanterar energikrävande uppgifter som t.ex. vilken sensor som ska kommunicera med vem samt vid vilken tidpunkt etc. Då kan sensorerna i nätverket fokusera på att utföra sina egna uppgifter tills dess att basstationen säger att uppgifterna ändrats.Simuleringar visar att vår plattform kan skicka upp till 97 % mera information till basstationen än en jämförbar plattform med samma energimängd. 88 % av våra sensorer är fortfarande vid liv när den andra plattformens sensorer förbrukat all sin energi.Ett exempel på hur dessa typer av nätverk kan användas är att övervaka patienters hälsa och kondition i sjukhus eller sjukhem. Patienter behöver inte ha en fast sängplats där en viss typ av medicinskt övervakningsinstrument finns tillgänglig utan kan placeras där det finns en ledig sängplats. Via trådlös kommunikation skickar sensorerna sedan hälsoinformation som t.ex. hjärtfrekvens och blodtryck till en basstation som i sin tur skickar vidare till ett centralt övervakningsinstrument någonstans på sjukhuset. Övervakningsinstrumentet behandlar informationen och larmar personal med rätt kompetens vid behov. Larmet kan skickas till en mobiltelefon eller en liten handdator som personalen alltid bär med sig. Med larmet skickas även information om var patienten befinner sig och all nödvändig data för att personalen snabbt ska kunna ställa en första diagnos. På detta sätt kan man spara in på antalet specialbyggda sängplatser och slippa dyrbara installationer av medicintekniska utrustningar knutna till en sängplats.
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