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Quick fault-tolerance detection method for monitoring abnormal event by wireless sensor network

A wireless sensor and abnormal event technology, applied in the field of Internet of Things, can solve problems such as poor timeliness, long response time, and large delay

Inactive Publication Date: 2014-05-28
CHINA UNIV OF GEOSCIENCES (WUHAN)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The advantage of this method is that when the node failure rate is low, the accuracy of detecting abnormal events is high, the false alarm rate is low, and the fault tolerance is good; however, the disadvantage of the existing MV method and its series of improved methods is the response time Long, large delay, poor timeliness
Because these methods use the spatial correlation of the monitoring values ​​of the nodes to achieve fault tolerance, although the reliability is improved, it is inevitable to prolong the response time for detecting abnormal events.

Method used

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  • Quick fault-tolerance detection method for monitoring abnormal event by wireless sensor network
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  • Quick fault-tolerance detection method for monitoring abnormal event by wireless sensor network

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Embodiment 1

[0045] Embodiment 1: The fast fault-tolerant detection method of wireless sensor network monitoring abnormal event of the present invention, its detection steps are as follows figure 1 As shown in the flow chart, it contains the following steps:

[0046] Step 1: The local node obtains raw monitoring data and converts it to binary readings ;Each sensor node obtains the original monitoring data of the monitoring object, and detects the alarm value λ according to the corresponding event t , convert the monitoring value of the current detection cycle into a binary reading . If the original monitoring data is less than λ t Converted to a binary reading of 0, then (expressed as a normal event); if the original monitoring data is greater than or equal to λ t converted to a binary reading of 1, then (indicated as exception events). Due to the impact of node failure, the monitoring data of the node may be wrong, causing the reading of the node to be wrong, 0 to 1 or 1 to 0, ...

Embodiment 2

[0074] Embodiment 2: In order to evaluate the usability and effectiveness of the FTV of the present invention, a simulation experiment was carried out on the method of the present invention.

[0075] Diffusion events are a class of events that widely exist in the real world, such as gas leaks, pollutant diffusion, and fires. Under the influence of external environmental factors, diffusion events will spread along certain specific directions and have an impact on the surrounding environment. In the diffusion direction of the event, the closer the area is to the event, the greater the impact of the event. The impact of such events on the surrounding environment is long-term, extensive and dynamic in both time and space. In the actual environment, diffuse anomaly events can be divided into two types: rising events and falling events. A rising event is characterized by an event value greater than the normal variation range of the attribute, while a falling event is characterized...

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Abstract

The invention relates to a quick fault-tolerance detection method for monitoring an abnormal event by a wireless sensor network, and belongs to the technical field of the Internet of things. The sensor network is formed by self-organizing a large number of low-end sensor nodes; each node has finite power energy, communication capacity, calculation capacity and storage capacity and is generally arranged in an unattended severe environment; the possibility that each node makes a mistake is extremely high; and if the node makes a mistake, the network probably misjudges an event in a monitoring region. According to the method, the states of the nodes are adaptively managed by using confidence level, and failed nodes are removed from the sensor network, so that the influence of the failed nodes on abnormal event detection is reduced; and furthermore, a sliding window matching mechanism is used for detecting the change tendency of node monitoring data, so that whether the nodes can detect the abnormal event is forecasted. A simulation test shows that the reliability and the timeliness of detecting the abnormal event are improved, and the method can be widely applied to the fields of safety production monitoring, geological disaster monitoring, environment pollution monitoring and the like.

Description

technical field [0001] The invention relates to a fast fault-tolerant detection method for monitoring abnormal events in a wireless sensor network, referred to as FTV for short, which is suitable for a wireless sensor network system with self-organizing characteristics, and belongs to the technical field of the Internet of Things. Background technique [0002] The Internet of Things has a wide range of uses, covering industrial and agricultural production, environmental monitoring, modern logistics, security and other fields. According to the forecast of the "China Market Intelligence Center", the scale of my country's Internet of Things industry will reach 800 billion yuan in 2013, and it will exceed 5 trillion yuan in 2020. The Internet of Things can integrate the physical world and the information world well, and fundamentally change the existing IT system. However, the large-scale industrialization of the Internet of Things still needs to solve some key problems, and on...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W24/04H04W84/18
Inventor 陈分雄王典洪徐朝玉田博邓慧丽张娇娇王登朵孔智韬牛博耸陈振华沈耀东陈春晖
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)