Method for detecting abnormal running state of lightweight embedded system

Abstract

The invention discloses a method for detecting an abnormal running state of a lightweight embedded system. The method comprises the steps of obtaining a node task execution sequence in a normal state;counting the one-step transfer frequency Mij of all tasks, and selecting to obtain a set M of high-frequency task transfer combinations; establishing a hypothesis testing method; setting a task window value w and a sample number n of u test statistics, and calculating a mean value mu0 of each group of high-frequency task transfer in all windows w; setting an expected anomaly detection confidenceprobability alpha, and querying the standard normal distribution function table according to the alpha to obtain a calculation anomaly value l; and inserting the l and the exception detection code corresponding to the exception discriminant into the corresponding position of the application source code, thereby detecting whether the application operation is exceptional or not. According to the method, the abnormal behavior occurring in the program execution process can be effectively detected, and the abnormal sequence can be accurately positioned.

Description

technical field [0001] The invention relates to the field of detection of embedded systems under the environment of wireless sensor networks, in particular to a method for detecting abnormal running states of light-weight embedded systems, which detects abnormal behaviors in the process of program execution. Background technique [0002] Wireless sensor networks are an important part of the Internet of Things. Wireless sensor networks are deployed in the real physical world to obtain information about the physical world. Many challenges. Usually, the deployment environment of wireless sensor networks is relatively harsh. In order to improve the availability of wireless sensor networks, people need more effective and convenient wireless sensor network status monitoring and abnormal diagnosis tools, and the status monitoring and abnormal diagnosis of wireless sensor networks after deployment are currently is very difficult. [0003] Anomalies in the operation of wireless sen...

AI Technical Summary

Problems solved by technology

[0005] Among the existing technologies mentioned above, the detection method of sensory node anomaly cannot accurately locate the location of the fault in the source code, or cannot find the abnormality of the source code in the execution state, which has obvious defects.

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