A Blockchain-Based Cloud Edge Fusion Computing Platform for the Smart Grid
Ying Gao, Sijie Su, Yandan Chen, Qiaofeng Pan, Xiping Hu · 2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics) · 2022
With the development of the smart grid, the number of access equipment capacity reached more than 100 million, resulting in long delays in the transmission of a large amount of data obtained from the terminal side to the cloud computing center. The emergence of powerful edge computing can greatly reduce the propagation delay, improve the management efficiency of IoT equipment in the smart grid, and reduce the communication delay between devices. However, due to decentralization, classical edge computing platforms face management and security challenges. In this paper, we propose a blockchain-based cloud edge fusion computing (BCEC) platform for controlling the smart grid, which integrates blockchain techniques to ensure the safety of the smart grid equipment. Specifically, we propose a three-level five-dimension credit scoring algorithm to ensure the security of the system. Through this algorithm, cloud computing and edge computing are combined, and the credit score of terminal equipment is allocated, taking into account the participation and security. Finally, we propose a time greedy allocation algorithm based on the Gini coefficient as a scheduling algorithm to ensure the fairness of system allocation and minimize the allocation delay. We deploy BCEC in the simulation environment for experimentation and the results show that BCEC can provide calculation services with low latency and high fairness for the smart grid system.