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JACIII Vol.22 No.7 pp. 1114-1119
doi: 10.20965/jaciii.2018.p1114
(2018)

Paper:

Soft Fault Detection Algorithms for Multi-Parallel Data Streams Under the Cloud Computing

Hongbing Meng

College of Information Engineering, Tarim University
Alar, Xinjiang 843300, China

Received:
April 26, 2018
Accepted:
June 4, 2018
Published:
November 20, 2018
Keywords:
cloud computing, multiple parallel, data stream, soft fault detection
Abstract
Soft Fault Detection Algorithms for Multi-Parallel Data Streams Under the Cloud Computing

Classification results of the method proposed in this paper

In the fault detection of multi-parallel data streams, the error probability of traditional methods is large, which cannot effectively meet the soft fault detection for multi-parallel data stream, causing the problem of low detection efficiency. A soft fault detection algorithm based on adaptive multi-parallel data stream is proposed. The soft fault feature in the data stream is extracted, and the adaptive soft fault detection algorithm is used to detect the fault of the multi-parallel data stream, which can overcome the disadvantages of traditional methods, effectively improve the efficiency, safety and the accuracy. Experimental results showed that the proposed method can effectively improve the efficiency of fault detection.

Cite this article as:
H. Meng, “Soft Fault Detection Algorithms for Multi-Parallel Data Streams Under the Cloud Computing,” J. Adv. Comput. Intell. Intell. Inform., Vol.22, No.7, pp. 1114-1119, 2018.
Data files:
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Last updated on Dec. 13, 2018