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

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.

[1]  Ching-Han Chen,et al.  High-level modeling and synthesis of smart sensor networks for Industrial Internet of Things , 2017, Comput. Electr. Eng..

[2]  Michele Zorzi,et al.  The internet of energy: a web-enabled smart grid system , 2012, IEEE Network.

[3]  Nei Kato,et al.  State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems , 2017, IEEE Communications Surveys & Tutorials.

[4]  Ching-Han Chen,et al.  Designing and Implementing a Lightweight WSN MAC Protocol for Smart Home Networking Applications , 2017, J. Circuits Syst. Comput..

[5]  Ioan Ungurean.  Industrial Internet of Things with Data Distribution Service for Real Time Systems , 2015 .

[6]  Hui Guo,et al.  A Survey on Emerging Computing Paradigms for Big Data , 2017 .

[7]  Ieee Beijing.  Internet of Things:Objectives and Scientific Challenges , 2011 .

[8]  Hua-Dong Ma,et al.  Internet of Things: Objectives and Scientific Challenges , 2011, Journal of Computer Science and Technology.

[9]  Ju Ren,et al.  Serving at the Edge: A Scalable IoT Architecture Based on Transparent Computing , 2017, IEEE Network.

[10]  Ke Xu,et al.  A tutorial on the internet of things: from a heterogeneous network integration perspective , 2016, IEEE Network.

[11]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[12]  Florian Ernst,et al.  Industry 4.0 / Industrial Internet of Things - Related Technologies and Requirements for a Successful Digital Transformation: An Investigation of Manufacturing Businesses Worldwide , 2015 .

[13]  Nei Kato,et al.  The Deep Learning Vision for Heterogeneous Network Traffic Control: Proposal, Challenges, and Future Perspective , 2017, IEEE Wireless Communications.

[14]  Ching-Han Chen,et al.  High-performance fieldbus application-specific integrated circuit design for industrial smart sensor networks , 2017, The Journal of Supercomputing.

[15]  Lei Shu,et al.  Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges , 2016, Sensors.