Wireless sensor network abnormality detection method based on space-time similarity

Abstract

The invention relates to a wireless sensor network abnormality detection method based on space-time similarity. The method comprises the following steps: obtaining a representative feature attribute set according to a feature set extraction algorithm; mapping the representative feature attribute set to a two-dimensional visible space, and obtaining visualization data; performing temporal similarity calculation on the visualization data according to temporal similarity, and obtaining a temporal similarity data model; and performing spatial similarity calculation on the wireless sensor network abnormality detection method based on space-time similarity. By adoption of the technical scheme provided by the invention, the abnormality detection in a sensor network is achieved, the features in the abnormality detection are extracted for detection, the contact between abnormal feature attributes is judged to provide a specific feasible scheme for obtaining an effective and high-accuracy abnormality detection result, and the network abnormality detection ability of processing dense nodes is available, so that the sensor network works more accurately in more complicated scenes.

Description

technical field [0001] The invention relates to the technical field of sensor network diagnosis, in particular to a wireless sensor network anomaly detection method based on time-space similarity. Background technique [0002] A sensor network is a wireless network composed of a large number of stationary or moving sensors in a self-organizing and multi-hop manner. Its purpose is to cooperatively perceive, collect, process and transmit detection information of sensing objects in the geographical area covered by the network, and report to users. It provides users with remote monitoring and control in a distributed computing environment. The main components of the sensor network include the sensor node (Sensor Node) and the base station node (Sink Node). Usually, the sensor node forms a communication network through a wireless multi-hop self-address form, and transmits the collected data back to the base station. Each sensor node is composed of data acquisition module, data p...

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Problems solved by technology

[0004] However, the above-mentioned method of abstracting and summarizing event data using a graph model has the disadvantage that for the abnormality of densely arranged sensor node groups, the disadvantage of anomaly detection performance will decrease exponentially with the increase of the number of nodes; the above-mentioned method based on feature selection Methods The method of detecting wireless sensor networks does not propose a specific and feasible plan for how to judge the relationship between abnormal features and obtain effective and high-accuracy abnormal detection results

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