Configurable Computing Systems for Enhanced Industrial Communication

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (15 June 2024) | Viewed by 2368

Special Issue Editor


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Guest Editor
Department of Information Engineering, University of Brescia, Brescia 25123, Italy
Interests: industrial real-time network; wireless sensor network; smart sensors; communication systems for smart grids; time synchronization; Linux-embedded programming; embedded systems; power quality; smart grids; energy systems; smart building; energy management system; electric vehicles; vehicle-to-vehicle communication
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Special Issue Information

Dear Colleagues,

Configurable computing systems refer to hardware and software platforms that can be customized to meet specific needs and requirements. These systems are increasingly being used to enhance industrial communication, enabling more efficient and effective data transfer and processing in industrial settings. In the context of industrial communication, configurable computing systems can be used to create customized interfaces between various industrial devices, such as sensors, actuators, and controllers. By configuring these systems to meet the specific needs of the industrial process, organizations can optimize the flow of data and improve the overall efficiency of their operations.

One key advantage of configurable computing systems is their flexibility. These systems can be reconfigured and updated as needed, allowing organizations to adapt to changing requirements and technologies. This flexibility also enables organizations to optimize their industrial communication systems over time, continually improving their operations and reducing costs. Another advantage of configurable computing systems is their ability to handle large volumes of data. With the growth of the Industrial Internet of Things (IIoT), organizations are generating more data than ever before. Configurable computing systems can help organizations manage this data and extract valuable insights that can inform decision making and improve operational efficiency.

This Special Issue welcomes theoretical papers, methodological studies, and empirical research (or combinations thereof) on the usage of configurable computing systems to enable the Industrial Internet of Things and sustainable wireless sensor network, to improve network security, reliability, and availability, and scheduling mechanisms to fulfil timing and reliability requirements dictated by industrial applications.

The topics of interest include, but are not limited to:

  • Industrial Internet of Thing;
  • Cyber Physical Systems;
  • Distributed measurement systems;
  • Neural Network;
  • Time synchronization mechanisms;
  • Real-time indoor localization systems;
  • Performance evaluation and modelling of communication systems and architectures;
  • Software Defined Networking (SDN);
  • Cloud and Fog computing in future factories;
  • Real-time communication standards;
  • Deterministic medium access schemes and real-time scheduling;
  • In-vehicle real-time communications;
  • Cooperating robot sensor networks.

Dr. Stefano Rinaldi
Guest Editor

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Keywords

  • industrial internet of thing
  • system on chip
  • FPGA
  • cyber security
  • artificial intelligence
  • cyber physical systems
  • configurable systems
  • neural network
  • cryptography
  • time synchronization mechanisms
  • real-time indoor localization systems
  • performance evaluation and modelling of communication systems and architectures
  • software defined networking (SDN)
  • cloud and fog computing in future factories
  • real-time communication standards
  • deterministic medium access schemes and real-time scheduling
  • in-vehicle real-time communications
  • cooperating robot sensor networks
  • 5G and beyond

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Published Papers (2 papers)

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Research

18 pages, 5713 KiB  
Article
Design and Implementation of Reconfigurable Array Adaptive Optoelectronic Hybrid Interconnect Shunting Network
by Bowen Yang, Yong Li, Chao Xi, Rui Shan, Yu Feng and Jiaying Luo
Electronics 2024, 13(9), 1668; https://doi.org/10.3390/electronics13091668 - 26 Apr 2024
Viewed by 774
Abstract
Addressing challenges regarding Hybrid Optoelectronic Network-on-Chip systems, such as congestion control, their limited adaptability, and their inability to facilitate optoelectronic co-simulation, this study introduces an adaptive hybrid optoelectronic interconnection shunt structure tailored for reconfigurable array processors. Within this framework, an adaptive shunt routing [...] Read more.
Addressing challenges regarding Hybrid Optoelectronic Network-on-Chip systems, such as congestion control, their limited adaptability, and their inability to facilitate optoelectronic co-simulation, this study introduces an adaptive hybrid optoelectronic interconnection shunt structure tailored for reconfigurable array processors. Within this framework, an adaptive shunt routing algorithm and a low-loss non-blocking five-port optical router are developed. Furthermore, an adaptive hybrid optoelectronic interconnection simulation model and a performance statistical model, established using SystemVerilog and Verilog, complement these designs. The experimental results showcase promising enhancements: the designed routing algorithm demonstrates an average 17.5% improvement in mitigating congestion at network edge nodes; substantial reductions in the required number of cross waveguides and micro-ring resonators for optical routers lead to an average path insertion loss of only 0.522 dB. Moreover, the hybrid optoelectronic interconnection performance statistical model supports the design of routing strategies and topology structures, enabling resource usage, power consumption, insertion loss, and other performance metrics to be accurately assessed. Full article
(This article belongs to the Special Issue Configurable Computing Systems for Enhanced Industrial Communication)
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16 pages, 4470 KiB  
Article
Enhancing Programmability in Next-Generation Networks: An Innovative Simulation Approach
by Jesús Calle-Cancho, Cristian Cruz-Carrasco, David Cortés-Polo, Jesús Galeano-Brajones and Javier Carmona-Murillo
Electronics 2024, 13(3), 532; https://doi.org/10.3390/electronics13030532 - 29 Jan 2024
Viewed by 1132
Abstract
With the advent of next-generation networks, it is crucial to persist in the research and development of key enabling technologies such as software-defined networking (SDN). This involves assessing prospective network deployments, mechanisms, or ideas; an undertaking performed by both network operators and academia [...] Read more.
With the advent of next-generation networks, it is crucial to persist in the research and development of key enabling technologies such as software-defined networking (SDN). This involves assessing prospective network deployments, mechanisms, or ideas; an undertaking performed by both network operators and academia to assess the advantages and limitations of the developed proposals related to programmable networks. In this context, simulators are envisioned as essential tools for replicating experiments, offering the required realism, adaptability, and scalability within a controlled environment. However, current solutions have limitations related to the SDN capabilities and indicators that allow for optimizing network performance, which is crucial for Beyond 5G (B5G) and 6G. To overcome this challenge, we propose SDNSimPy, a Python-based simulation framework built on a discrete event simulator. The proposed simulator features a modular architecture with various functional abstractions related to programmable networks, which have been partitioned into distinct modules to streamline its development and facilitate future extensions. Moreover, SDNSimPy has undergone a verification phase to check its implementation. Results obtained from the simulator reveal a significant distinction in the operation modes (proactive and reactive) with respect to end-to-end delay. This parameter is crucial in Beyond 5G (B5G) services and can impact the quality of service (QoS) of network communications. Full article
(This article belongs to the Special Issue Configurable Computing Systems for Enhanced Industrial Communication)
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