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Electronics
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Advances in Embedded and Distributed System Design
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Advances in Embedded and Distributed System Design

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 12571

Special Issue Editors

Prof. Dr. Juan Carlos López

E-Mail Website
Guest Editor
School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain
Interests: computer architecture; distributed systems; reconfigurable systems
Dr. Jesús Barba

E-Mail Website
Guest Editor
School of Computer Science, University of Castilla-La Mancha, 13071 Ciudad Real, Spain
Interests: computer architecture; distributed systems; reconfigurable systems

Special Issue Information

Dear Colleagues,

Embedded systems have been one of the key enablers of the change of our world and society during the past few decades, and they are called to play a prominent role in the future.

On top of that, significant advances in network technology, especially the rise of wireless communications, have contributed to the ubiquity of all sorts of devices, running with increasingly smarter and more sophisticated functionality. We tend to forget that they are an indissoluble part of reality, becoming indispensable in our lives.

Today, most embedded systems are, in turn, connected and decentralized, leading a technological revolution that builds markets or transforms existing ones. Concepts and visions of the future we want—such as Internet of Things (and eventually, the Internet of Everything), Autonomous and Connected Cars, Industry 4.0 or Smart Cities—would not be possible without embedded and distributed systems.

This Special Issue aims to cover the most recent advances related to the design and programming of embedded and distributed systems, covering all hardware and software technologies. We encourage researchers and engineers from both the academia and industry to share with the readers their visions and latest contributions to the development of next-generation solutions, with special emphasis on their applicability to real-life.

Prof. Dr. Juan Carlos López
Dr. Jesús Barba
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Design methodologies and tools for embedded systems: system-level synthesis, design space exploration and simulation
  • Verification and validation
  • Compiler technology for embedded systems
  • Heterogeneous architectures and co-design
  • Smart embedded systems and embedded intelligence
  • Security and robustness
  • Power efficient methods and algorithms
  • Energy harvesting embedded systems
  • Edge and fog computing architectures
  • Collaborative embedded system
  • Cyberphysical systems and systems-of-systems
  • Embedded operating systems and middleware
  • Self-aware, self-adaptive, and autonomous systems
  • AI methods and algorithms in embedded and distributed systems
  • Applications of embedded and distributed systems

Published Papers (3 papers)

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Research

22 pages, 5616 KiB  
Article
RF Acquisition System Based on μTCA for Testing of High-Gradient Acceleration Cavities
by Abraham Menéndez, Daniel Esperante, Raimundo García-Olcina, José Torres, Joaquín Pérez-Soler, Ricardo Marco, Benito Gimeno, Julio Martos and Jesús Soret
Electronics 2022, 11(5), 720; https://doi.org/10.3390/electronics11050720 - 25 Feb 2022
Viewed by 3600
Abstract
The radio frequency (RF) laboratory hosted in the Corpuscular Physics Institute (IFIC) of the University of Valencia is designed to house a high-power and high-repetition-rate facility to test normal conduction RF accelerator cavities in the S-Band (2.9985 GHz) in order to perform R&D [...] Read more.
The radio frequency (RF) laboratory hosted in the Corpuscular Physics Institute (IFIC) of the University of Valencia is designed to house a high-power and high-repetition-rate facility to test normal conduction RF accelerator cavities in the S-Band (2.9985 GHz) in order to perform R&D activities related to particle accelerator cavities. The system, which manages the entire process of RF signal generation, data acquisition and closed-loop control of the laboratory, is currently based on a modular and compact PXI platform system. This contribution details the development of a platform with similar features, but which is based on open architecture standards at both the hardware and software level. For this purpose, a complete system based on the μTCA platform has been developed. This new system must be able to work with accelerator cavities at other operating frequencies, such as 750 MHz, as well as to explore different options at firmware and software levels based on open-source codes. Full article
(This article belongs to the Special Issue Advances in Embedded and Distributed System Design)
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15 pages, 5257 KiB  
Article
On-Device Training of Machine Learning Models on Microcontrollers with Federated Learning
by Nil Llisterri Giménez, Marc Monfort Grau, Roger Pueyo Centelles and Felix Freitag
Electronics 2022, 11(4), 573; https://doi.org/10.3390/electronics11040573 - 14 Feb 2022
Cited by 15 | Viewed by 5765
Abstract
Recent progress in machine learning frameworks has made it possible to now perform inference with models using cheap, tiny microcontrollers. Training of machine learning models for these tiny devices, however, is typically done separately on powerful computers. This way, the training process has [...] Read more.
Recent progress in machine learning frameworks has made it possible to now perform inference with models using cheap, tiny microcontrollers. Training of machine learning models for these tiny devices, however, is typically done separately on powerful computers. This way, the training process has abundant CPU and memory resources to process large stored datasets. In this work, we explore a different approach: training the machine learning model directly on the microcontroller and extending the training process with federated learning. We implement this approach for a keyword spotting task. We conduct experiments with real devices to characterize the learning behavior and resource consumption for different hyperparameters and federated learning configurations. We observed that in the case of training locally with fewer data, more frequent federated learning rounds more quickly reduced the training loss but involved a cost of higher bandwidth usage and longer training time. Our results indicate that, depending on the specific application, there is a need to determine the trade-off between the requirements and the resource usage of the system. Full article
(This article belongs to the Special Issue Advances in Embedded and Distributed System Design)
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18 pages, 4445 KiB  
Article
FPGA Implementation of Image Ordering and Packing Algorithm for TuMag Camera
by Eduardo Magdaleno, Manuel Rodríguez Valido, David Hernández, María Balaguer, Basilio Ruiz Cobo and David Díaz
Electronics 2021, 10(14), 1706; https://doi.org/10.3390/electronics10141706 - 16 Jul 2021
Cited by 1 | Viewed by 2147
Abstract
The TuMag instrument is a Tunable Magnetograph that has been designed to measure the magnetic field of the sun. This instrument and others will be connected to a telescope that will be sent into the stratosphere using a balloon for an uninterrupted observation [...] Read more.
The TuMag instrument is a Tunable Magnetograph that has been designed to measure the magnetic field of the sun. This instrument and others will be connected to a telescope that will be sent into the stratosphere using a balloon for an uninterrupted observation of the sun for four days in the summer of 2022. The TuMag camera is a new development for implementing the image detector of the instrument. It is based on the GPIXEL GSENSE400-BSI scientific CMOS image sensor and an FPGA device in charge of controlling the image sensor, configuring it and grabbing images. FPGA device consists of an array of Configurable Logic Blocks. However, the sensor does not supply the image data in a row-by-column format. This task has to be done in the FPGA that controls the sensor because the frame grabber has a significant workload with the control of all the instruments, the telescope, the refrigeration, the navigation, and so on. This work describes the FPGA implementation of Image Ordering and Packing algorithm for TuMag Camera concerning the real-time ordering of the images before grabbing and sending to the Data Processing Unit. Full article
(This article belongs to the Special Issue Advances in Embedded and Distributed System Design)
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