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Research on Internet of Things security architecture based on fog computing

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  • Trung Dong Mai

Abstract

The traditional data processing of the Internet of Things is concentrated in cloud computing, and its huge number of devices and massive real-time data transmission are extremely stressful on network bandwidth and cloud computing data centers. Fog computing is the infrastructure that can use processing power anywhere in the cloud. Virtual computing extends the power of cloud computing to the edge of the network, enabling any computing device to host and process software services, analyzing and storing data closer to where data are generated. The architecture of the fog computing brings enormous processing power. Since its processing power is often located near the required equipment, the distance of data transmission is reduced and the delay is reduced. This article explores how to use the fog computing layer between the cloud data center and the end node layer to store and process large amounts of local data in a timely manner, speeding decision making and enabling Internet of Things manufacturers and software developers to limit their ability to send data. They reduced cloud computing costs and built a reasonable security architecture.

Suggested Citation

  • Trung Dong Mai, 2019. "Research on Internet of Things security architecture based on fog computing," International Journal of Distributed Sensor Networks, , vol. 15(11), pages 15501477198, November.
    • Handle: RePEc:sae:intdis:v:15:y:2019:i:11:p:1550147719888166
    DOI: 10.1177/1550147719888166
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    References listed on IDEAS

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    1. FengChun Liu & YaLou Liu & DongHao Jin & XueYong Jia & TingTing Wang, 2018. "Research on Workshop-Based Positioning Technology Based on Internet of Things in Big Data Background," Complexity, Hindawi, vol. 2018, pages 1-11, October.
    2. Hanliang Fu & Zhaoxing Li & Zhijian Liu & Zelin Wang, 2018. "Research on Big Data Digging of Hot Topics about Recycled Water Use on Micro-Blog Based on Particle Swarm Optimization," Sustainability, MDPI, vol. 10(7), pages 1-15, July.
    3. Daopeng Wang & Jifei Fan & Hanliang Fu & Bing Zhang, 2018. "Research on Optimization of Big Data Construction Engineering Quality Management Based on RNN-LSTM," Complexity, Hindawi, vol. 2018, pages 1-16, July.
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