Wang Jiye

Application of the Snowflake Structure in the Network Structure of Electric Power Enterprise Data Center

The network structure of electric power enterprise data center is one of todays data center researches, which aims at creating a better, safer and more efficient network structure. The main content of this article involves the application of a new-type network structure of data center-snowflake structure in electric power enterprises. First of all, it introduces the network structures of todays data centers and the snowflake network structure. Then it illustrates three characteristics of snowflake structure in terms of transmission bandwidth, throughput bottlenecks and network delay, and compares snowflake structure with Dcell and Bcube in order to highlight the superiority of snowflake structure. Finally, according to the characteristics of snowflake structure, it describes the research on the application of snowflake structure in the electric power enterprise data center.

Adaptive Multi-scale Edge Detection in the EMD Domain

A multi-scale edge detection method in the empirical mode decomposition (EMD) domain using the consistent EMD method to decompose the reference noise to adaptively estimate the noise threshold is proposed to detect the edges of noisy signals with different signal to noise ratios. The new algorithm first calculates the slope of the EMD residuals in scales. Second, it eliminates the noise in the slope signal by thresholding, and the noise threshold is estimated according to the mean square value of the reference noise. At last, the edge information is output by the way of the spatial consistence test. Simulation results show that, the adaptive multi-scale edge detection method in the EMD domain can accurately detect the signal edges, and suppress the noise.