KEYWORDS: Clouds, Internet, Sensors, Intelligent sensors, Data centers, Data processing, Data storage, Data modeling, Data communications, Computing systems
Since the construction of energy internet has been continuously moving forward, various sensors that are involved in the energy system tend to increase dramatically. Massive data obtained from those sensors impose huge pressure on the transmission system and heavy computation load on the centre station, while traditional data processing approaches have suffered from undesirable data quality, data losses and format inconsistency. The introduction of edge computing is to redefine the framework of intelligent perception system by achieving data processing locally, and hence optimize the system through cloud-edge collaboration mechanism. In this paper, the optimized transmission approach for multiparameter intelligent perception has been given, after which the design methodology for its edge computing algorithm has been proposed, including data unification, data identification and distributed swarm intelligence.
KEYWORDS: Data centers, Computer security, Symmetric-key encryption, Energy efficiency, Safety, Data transmission, Network security, Data processing, Environmental sensing, Data conversion
In view of the problems of low security, low efficiency of encryption transmission and high energy consumption of data encryption transmission in traditional methods, an AES based sensitive data encryption transmission method for energy big data center is proposed. The encryption round operation of AES algorithm is used for the encryption round operation result. Based on the encryption round operation result of AES algorithm, the secret key data matrix is generated. When data is encrypted, the data matrix is traversed at any node of the encryption end, and the key data matrix is generated again. On this basis, Zigzag permutation method is used for data transmission to complete data encryption transmission. Experimental results show that the security factor and execution efficiency of the proposed method are higher than those of traditional methods, and the energy consumption of data encryption transmission is the lowest, which indicates that the proposed method can ensure the quality of sensitive data encryption transmission in energy big data center.
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