Artificial intelligence-based early warning and self-healing technology for distribution edge IoT networks
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Abstract:
The distribution of IoT (Internet of Things) is the last link in the construction of ubiquitous power IoT. It possesses characteristics such as short power supply path and high load density, which bring about significant challenges in terms of protection and control. To address these challenges, the establishment of an early warning and self-healing strategy for the distribution network is crucial, enabling the formation of a smart distribution network with flexible operation mode, timely fault warning and perfect fault self-healing. This paper proposes a security defense technology framework applicable to the firmware of the distribution IoT edge network. The framework protects the reliability matrix of each firmware present in the edge devices, while the edge devices are interconnected through the edge servers, forming a technical solution for distribution edge IoT that incorporates security warning and self-healing capabilities. Finally, the feasibility of this scheme is verified by simulation experiments conducted under different environmental conditions.
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Supported by National Natural Science Foundation of China (62072065), and Science and Technology Projects of China Southern Power Grid (GDKJXM20198151).
