Multi-Threaded Data-Scrambling Techniques Using Reduced on-Chip Memory for Light-Weight Embedded Systems

With the increasing importance of data acquisition and processing in various applications, it is essential for systems using reduced memory to efficiently fulfill these requirements. In this study, we propose a method for high-speed data acquisition and signal processing in reduced memory by utilizing an ARM Cortex-M3-based STM32F103 Nucleo board. The proposed system consists of an analog-to-digital converter (ADC), two buffers (Buffer1 and Buffer2), and a universal asynchronous receiver/transmitter (UART) module, and the four modules are threaded to optimize the process of data acquisition, signal processing, and data transmission. We set the ADC and signal processing to operate at maximum speed and used minimal memory in the process. Our results show that the proposed system can effectively collect and process data using reduced memory in embedded systems.

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Published
2024-10-16
DOI
https://doi.org/10.1109/ictc62082.2024.10827600
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-Threaded Data-Scrambling Techniques Using Reduced on-Chip Memory for Light-Weight Embedded Systems

Daejin Park, Jongyun Byeon
Parallel Computing and Optimization Techniques
article

Multi-Threaded Data-Scrambling Techniques Using Reduced on-Chip Memory for Light-Weight Embedded Systems

Daejin Park, Jongyun Byeon
article en

Abstract

With the increasing importance of data acquisition and processing in various applications, it is essential for systems using reduced memory to efficiently fulfill these requirements. In this study, we propose a method for high-speed data acquisition and signal processing in reduced memory by utilizing an ARM Cortex-M3-based STM32F103 Nucleo board. The proposed system consists of an analog-to-digital converter (ADC), two buffers (Buffer1 and Buffer2), and a universal asynchronous receiver/transmitter (UART) module, and the four modules are threaded to optimize the process of data acquisition, signal processing, and data transmission. We set the ADC and signal processing to operate at maximum speed and used minimal memory in the process. Our results show that the proposed system can effectively collect and process data using reduced memory in embedded systems.

Kyungpook National University (KR)
Ministry of Education, National Research Foundation of Korea, IC Design Education Center
Affordable and clean energy
Openalex Percentile: Top 72%
Parallel Computing and Optimization Techniques
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Multi-Threaded Data-Scrambling Techniques Using Reduced on-Chip Memory for Light-Weight Embedded Systems — Daejin Park, Jongyun Byeon · (2024) | TGRS Research Map | TGRS