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Based embedded software fault-tolerant data flow anomaly detection

Author: XuLingXiang
Tutor: FanShouWen
School: University of Electronic Science and Technology
Course: Mechanical Design and Theory
Keywords: Fault-tolerant Error correction Data stream Regression analysis Rewind Reply Cluster analysis
CLC: TP368.1
Type: Master's thesis
Year: 2011
Downloads: 13
Quote: 0
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Abstract


Modern mechanical and electrical products in the more complex functions at the same time, increasing its safety and reliability requirements. Software as an important part of the mechanical and electrical products, and its reliability directly determine the quality of the mechanical and electrical products. The main line to improve the software's reliability and safety study of the mechanical and electrical products, from the perspective of the software data flow analysis, a more in-depth and systematic study of the data stream based anomaly detection software fault-tolerant error correction technology. Proposed a new data stream based anomaly detection software watchdog technology and rollback recovery technology software fault-tolerant error correction method for software system failure may occur. The method periodic backup of the target program, through the extraction of the target program in a group of related variables to establish the data flow analysis model investigation wherein outliers i.e. error point, using the method of detecting abnormality of the data stream. When found the error of the target program is running, the watchdog to force the program to jump to the backup point Rewind to the normal state of the last backup of the target program to achieve fault-tolerant error correction software transient fault. Proposed the framework of the implementation of the software fault-tolerant error correction strategy, operational procedures, bivariate regression model and outlier detection algorithm based on least squares support vector machine. Binary function, for example, binary regression model proposed outlier detection algorithm simulation, simulation results verify the correctness of the regression model and the effectiveness of outlier detection algorithm. Biased recent developments based on distance data flow anomaly detection algorithm, which is based on the clustering thinking of the abnormality detecting method, by calculating the distance of the detection data and cluster centers to determine abnormalities, and in accordance with the characteristics of the data flow has been improved, the abnormality detection of the data stream can be effectively realized. The algorithm is simple and fast calculation, choice is adaptive threshold, to improve the accuracy of detection, simulation experiments to verify the effectiveness of the algorithm. Designed as the core data flow anomaly detection algorithm based on data flow anomaly detection software fault-tolerant error correction experimental program to set up the experiment platform, software fault-tolerant error correction experimental study. The experimental results show that this paper, the fault-tolerant strategy well to achieve fault-tolerant software error correction, the above studies provide new solutions for software fault-tolerant error correction.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Micro-computer > A variety of micro-computer > Microprocessor
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