Rapid prototyping of distributed embedded systems as a part of Internet of Things

Raskin, Denis; Vassiliev, Alexei; Samarin, Vasili; Cabezas, Diego; Hiererra, Siti Elda; Kurniawan, Yohannes

doi:10.1016/j.procs.2018.08.202

Cited by 5 publications

(1 citation statement)

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“…The comprehensive survey of categorizing IoT devices into low, medium, and the high-end application was presented in [32][33][34]. The characteristics of IoT systems that differentiate from other linked systems are discussed [35].…”

Section: Figure 3 Things and End-user Device Networkingmentioning

confidence: 99%

Systematic Approach for State-of-the-Art Architectures and System-on-Chip Selection for Heterogeneous IoT Applications

et al. 2021

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The Internet of Things (IoT) refers to a network of physical devices, which collects data and processes into a system without human intervention. In the commercialized market, IoT architectures are upgrading day by day to reduce data transmission costs, latency, and bandwidth usage for various application requirements. The extensively available IoT architectures and their specification resist the researchers to select a system-on-chip (SoC) for heterogeneous IoT applications. This paper seeks to comprehend the various IoT device specifications and their characteristics to support multiple applications. Moreover, microprocessor architectures and their components are detailed to facilitate developer knowledge in advanced methodology and technology. The various instructions set architectures (ISA) are implemented in a Zynq-7000 (xc7Zz20clg484-1) FPGA device to examine the feasibility of design space requirements for real-time hardware execution. To select specific system-on-chip (SoC) architecture for heterogeneous IoT applications, a genetic algorithm (GA) based optimization method is implemented in MATLAB. The proposed algorithm identifies the optimized SoC architecture concerning device parameters such as a clock, cache, RAM space, external storage, network support, etc. Further, the confusion matrix method evaluates the proposed algorithm's accuracy, which yields 84.62% accuracy. The outcome of SoCs attained through the GA are tested by analyzing their execution time and performance using various evaluation benchmarks. This article helps the researchers and field engineers to comprehend the microarchitecture device configurations and to identify the superior SoC for next-generation IoT practices.INDEX TERMS Internet of Things, Microprocessors, System-on-chip, Heterogeneous Architectures, and Edge Computing.

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