Main Trend Extraction of the Storage Volume for Internet Data Center

Author(s):  
Bei-Bei Miao ◽  
Chao Dou ◽  
Xue-Bo Jin
2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Beibei Miao ◽  
Chao Dou ◽  
Xuebo Jin

The storage volume of internet data center is one of the classical time series. It is very valuable to predict the storage volume of a data center for the business value. However, the storage volume series from a data center is always “dirty,” which contains the noise, missing data, and outliers, so it is necessary to extract the main trend of storage volume series for the future prediction processing. In this paper, we propose an irregular sampling estimation method to extract the main trend of the time series, in which the Kalman filter is used to remove the “dirty” data; then the cubic spline interpolation and average method are used to reconstruct the main trend. The developed method is applied in the storage volume series of internet data center. The experiment results show that the developed method can estimate the main trend of storage volume series accurately and make great contribution to predict the future volume value. 



Author(s):  
Terry M.F. Tsang ◽  
Thomas M.W. Yeung ◽  
Dickson K.W. Chiu ◽  
Haiyang Hu ◽  
Yi Zhuang ◽  
...  

Author(s):  
YI-KUEI LIN ◽  
CHENG-FU HUANG

Quality of the received data at the sink can be based on packet delay, packet errors, packet loss, etc. From the viewpoint of quality of service (QoS), the packet unreliability (PU) and transmission time are both of critical attributes to assess internet quality for supervisor and customers. A computer system is usually modeled as a network topology with arcs and vertices where each arc denotes a transmission medium and each vertex represents an Internet data center. Due to failure, partial failure, maintenance, etc., each component (arc or vertex) should be considered as stochastic. The network with imperfect vertices is more complex to evaluate the reliability issue because vertex failure results in the disablement of adjacent arcs. Such a network named a stochastic imperfect vertex computer network (SIVCN) is addressed in this paper. We study how the data can be delivered through multiple minimal paths simultaneously within both permitted PU and time constraint. A solution procedure comprising two efficient algorithms is proposed to assess transmission reliability accordingly.


Author(s):  
Du-Hwan Kim ◽  
Taesik Yu ◽  
Hyosung Kim ◽  
Hyungsoo Mok ◽  
Kyung-Seok Park

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