Edge Computing Gateway of the Industrial Internet of Things Using Multiple Collaborative Microcontrollers

被引：106

作者：

Chen, Ching-Han ^{[1
]}

Lin, Ming-Yi ^{[2
,3
]}

Liu, Chung-Chi ^{[4
]}

机构：

[1] Natl Cent Univ, Dept CSIE, Taoyuan, Taiwan

[2] Army Acad ROC, Dept Comp Sci & Commun Engn, Taoyuan, Taiwan

[3] Natl Cent Univ, Taoyuan, Taiwan

[4] Asrock, Taipei, Taiwan

来源：

IEEE NETWORK | 2018年 / 32卷 / 01期

关键词：

Computational efficiency - Data acquisition - Electric power utilization - Network layers - Scalability - Gateways (computer networks) - Information management - Field programmable gate arrays (FPGA) - Edge computing - Green computing;

D O I：

10.1109/MNET.2018.1700146

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

An Internet of Things gateway serves as a key intermediary between numerous smart things and their corresponding cloud networking servers. A typical conventional gateway system uses a high-level embedded microcontroller (MCU) as its core; that MCU performs low-level perception-layer device network management, upper-level cloud server functions, and remote mobile computation services. However, in edge computing, many factors need to be considered when designing an IoT gateway, such as minimizing the response time, the power consumption, and the bandwidth cost. Regarding system scalability, computational efficiency, and communication efficiency, solutions that use a single MCU cannot deliver IoT functionality such as big data collection, management, real-time communication, expandable peripherals, and various other services. Therefore, this article proposes an innovative multi-MCU system framework combining a field-programmable-gate-array-based hardware bridge and multiple scalable MCUs to realize an edge gateway of a smart sensor fieldbus network. Through distributed and collaborative computing, the multi-MCU edge gateway can efficiently perform fieldbus network management, embedded data collection, and networking communication, thereby considerably reducing the real-time power consumption and improving scalability compared to the existing industrial IoT solutions.

引用

页码：24 / 32

页数：9

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