Novel algorithms for open-loop and closed-loop scheduling of real-time tasks in multiprocessor systems based on execution time estimation

Author(s):  
R. Al-Omari ◽  
G. Manimaran ◽  
M.V. Salapaka ◽  
A.K. Somani
2021 ◽  
Author(s):  
Jessica Junia Santillo Costa ◽  
Romulo Silva de Oliveira ◽  
Luis Fernando Arcaro

2020 ◽  
Vol 5 (2) ◽  
pp. 561-575
Author(s):  
Behnam Nouri ◽  
Ömer Göksu ◽  
Vahan Gevorgian ◽  
Poul Ejnar Sørensen

Abstract. The electrical test and assessment of wind turbines go hand in hand with standards and network connection requirements. In this paper, the generic structure of advanced electrical test benches, including grid emulator or controllable grid interface, wind torque emulator, and device under test, is proposed to harmonize state-of-the-art test sites. On the other hand, modern wind turbines are under development towards new features, concerning grid-forming, black-start, and frequency support capabilities as well as harmonic stability and control interaction considerations, to secure the robustness and stability of renewable-energy-based power systems. Therefore, it is necessary to develop new and revised test standards and methodologies to address the new features of wind turbines. This paper proposes a generic test structure within two main groups, including open-loop and closed-loop tests. The open-loop tests include the IEC 61400-21-1 standard tests as well as the additional proposed test options for the new capabilities of wind turbines, which replicate grid connection compliance tests using open-loop references for the grid emulator. In addition, the closed-loop tests evaluate the device under test as part of a virtual wind power plant and perform real-time simulations considering the grid dynamics. The closed-loop tests concern grid connection topologies consisting of AC and HVDC, as well as different electrical characteristics, including impedance, short-circuit ratio, inertia, and background harmonics. The proposed tests can be implemented using available advanced test benches by adjusting their control systems. The characteristics of a real power system can be emulated by a grid emulator coupled with real-time digital simulator systems through a high-bandwidth power-hardware-in-the-loop interface.


2021 ◽  
Vol 15 ◽  
Author(s):  
Neethu Robinson ◽  
Tushar Chouhan ◽  
Ernest Mihelj ◽  
Paulina Kratka ◽  
Frédéric Debraine ◽  
...  

Several studies in the recent past have demonstrated how Brain Computer Interface (BCI) technology can uncover the neural mechanisms underlying various tasks and translate them into control commands. While a multitude of studies have demonstrated the theoretic potential of BCI, a point of concern is that the studies are still confined to lab settings and mostly limited to healthy, able-bodied subjects. The CYBATHLON 2020 BCI race represents an opportunity to further develop BCI design strategies for use in real-time applications with a tetraplegic end user. In this study, as part of the preparation to participate in CYBATHLON 2020 BCI race, we investigate the design aspects of BCI in relation to the choice of its components, in particular, the type of calibration paradigm and its relevance for long-term use. The end goal was to develop a user-friendly and engaging interface suited for long-term use, especially for a spinal-cord injured (SCI) patient. We compared the efficacy of conventional open-loop calibration paradigms with real-time closed-loop paradigms, using pre-trained BCI decoders. Various indicators of performance were analyzed for this study, including the resulting classification performance, game completion time, brain activation maps, and also subjective feedback from the pilot. Our results show that the closed-loop calibration paradigms with real-time feedback is more engaging for the pilot. They also show an indication of achieving better online median classification performance as compared to conventional calibration paradigms (p = 0.0008). We also observe that stronger and more localized brain activation patterns are elicited in the closed-loop paradigm in which the experiment interface closely resembled the end application. Thus, based on this longitudinal evaluation of single-subject data, we demonstrate that BCI-based calibration paradigms with active user-engagement, such as with real-time feedback, could help in achieving better user acceptability and performance.


2014 ◽  
Vol 651-653 ◽  
pp. 624-629
Author(s):  
Liang Liang Kong ◽  
Lin Xiang Shi ◽  
Lin Chen

Most embedded systems are real-time systems, so real-time is an important performance metric for embedded systems. The worst-case execution time (WCET) estimation for embedded programs could satisfy the requirement of hard real-time evaluation, so it is widely used in embedded systems evaluation. Based on sufficient survey on the progress of WCET estimation around the world, it proposes a new classification of WCET estimation. After introducing the principle of WCET estimation, it mainly demonstrates various types of technologies to estimate WCET and classifies them into two main streams, namely, static and dynamic WCET estimations. Finally, it shows the development of WCET analysis tools.


2018 ◽  
Vol 1 (1) ◽  
pp. 178-186 ◽  
Author(s):  
Sevil Serttaş ◽  
Veysel Harun Şahin

Real-time systems are widely used from the automotive industry to the aerospace industry. The scientists, researchers, and engineers who develop real-time platforms, worst-case execution time analysis methods and tools need to compare their solutions to alternatives. For this purpose, they use benchmark applications. Today many of our computing systems are multicore and/or multiprocessor systems. Therefore, to be able to compare the effectiveness of real-time platforms, worst-case execution time analysis methods and tools, the research community need multi-threaded benchmark applications which scale on multicore and/or multiprocessor systems. In this paper, we present the first version of PBench, a parallel, real-time benchmark suite. PBench includes different types of multi-threaded applications which implement various algorithms from searching to sorting, matrix multiplication to probability distribution calculation. In addition, PBench provides single-threaded versions of all programs to allow side by side comparisons.


2021 ◽  
Author(s):  
Takayuki Onojima ◽  
Keiichi Kitajo

We propose a novel method to estimate the instantaneous oscillatory phase to implement a real-time system for closed-loop sensory stimulation in electroencephalography (EEG) experiments. The method uses Kalman filter-based prediction to estimate current and future EEG signals. We tested the performance of our method in a real-time situation. We demonstrate that the performance of our method shows higher accuracy in predicting the EEG phase than the conventional autoregressive model-based method. A Kalman filter allows us to easily estimate the instantaneous phase of EEG oscillations based on the automatically estimated autoregressive model implemented in a real-time signal processing machine. The proposed method has a potential for versatile applications targeting the modulation of EEG phase dynamics and the plasticity of brain networks in relation to perceptual or cognitive functions.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Miguel Angrick ◽  
Maarten C. Ottenhoff ◽  
Lorenz Diener ◽  
Darius Ivucic ◽  
Gabriel Ivucic ◽  
...  

AbstractSpeech neuroprosthetics aim to provide a natural communication channel to individuals who are unable to speak due to physical or neurological impairments. Real-time synthesis of acoustic speech directly from measured neural activity could enable natural conversations and notably improve quality of life, particularly for individuals who have severely limited means of communication. Recent advances in decoding approaches have led to high quality reconstructions of acoustic speech from invasively measured neural activity. However, most prior research utilizes data collected during open-loop experiments of articulated speech, which might not directly translate to imagined speech processes. Here, we present an approach that synthesizes audible speech in real-time for both imagined and whispered speech conditions. Using a participant implanted with stereotactic depth electrodes, we were able to reliably generate audible speech in real-time. The decoding models rely predominately on frontal activity suggesting that speech processes have similar representations when vocalized, whispered, or imagined. While reconstructed audio is not yet intelligible, our real-time synthesis approach represents an essential step towards investigating how patients will learn to operate a closed-loop speech neuroprosthesis based on imagined speech.


Sign in / Sign up

Export Citation Format

Share Document