Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things

2021 ◽  
Vol 68 ◽  
pp. 102779
Author(s):  
Khalid Haseeb ◽  
Ikram Ud Din ◽  
Ahmad Almogren ◽  
Imran Ahmed ◽  
Mohsen Guizani
Author(s):  
Matthew N. O. Sadiku ◽  
Mahamadou Tembely ◽  
Sarhan M. Musa

Fog computing (FC) was proposed in 2012 by Cisco as the ideal computing model for providing real-time computing services and storage to support the resource-constrained Internet of Things (IoT) devices. Thus, FC may be regarded as the convergence of the IoT and the Cloud, combining the data-centric IoT services and pay-as-you-go characteristics of clouds.  This paper provides a brief introduction of fog computing.


2012 ◽  
Vol 7 (7) ◽  
Author(s):  
Benjun Guo ◽  
Jianhong Gan ◽  
Jingwen Su ◽  
Yuewen Hu ◽  
Jun Lu

2021 ◽  
Vol 2108 (1) ◽  
pp. 012053
Author(s):  
Xiaohua Zhang ◽  
Wenxiang Xue ◽  
Shuyuan Wang ◽  
Yi Lu ◽  
Hui Wang

Abstract Current monitoring methods of transmission line operation status can not obtain real-time data of distributed distribution transmission line, which leads to a large error in monitoring results. Therefore, a multi-state on-line monitoring method based on power Internet of Things is proposed. Using the gateway of power internet of things to set up network control access mode, build edge computing model, and using AD chip of ADS8365W5300 to obtain the real-time data of massive distributed distribution network, then make a decision on the fault after processing and analyzing the data. This paper constructs an edge computing model which can complete the data processing and analysis in the edge node, and designs the deployment of the edge computing model. By evaluating the faults in the dynamic incremental fault set, the risk state of transmission line in the danger control area is obtained, and a multi-state on-line monitoring method is designed. The experimental results show that the proposed method can monitor the transmission line running state accuratel


2012 ◽  
Vol 7 (1) ◽  
Author(s):  
Zhikui Chen ◽  
Haozhe Wang ◽  
Yang Liu ◽  
Fanyu Bu ◽  
Zhe Wei

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