Identification method for anomalous points of cooperative synchronization in distributed network

A distributed network and identification method technology, applied in the field of abnormal point identification, can solve the problem of low real-time performance, achieve the effect of avoiding excessive dependence, high accuracy, and realizing rapid positioning

Active Publication Date: 2014-05-21
XIAMEN UNIV
View PDF1 Cites 24 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0014] Aiming at the shortcomings of the traditional centralized positioning method with low real-time performance, the present invention proposes a method for identifying synchronous abnormal points in a distributed network, which is fully connected (without isolated nodes) when the network is static (the network topology remains unchanged) In this case, with the clock synchronization process as the background, the bad point positioning process is distributed to each network communication node, avoiding the excessive dependence of the traditional centralized positioning method on the reference node, and realizing the rapid positioning of abnormal nodes in the wireless sensor network

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Identification method for anomalous points of cooperative synchronization in distributed network
  • Identification method for anomalous points of cooperative synchronization in distributed network
  • Identification method for anomalous points of cooperative synchronization in distributed network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] Assuming that there are N nodes in the network, we can choose the normal node i, and pass the formula:

[0039] t i (n+1)=ω i1 t 1 (n)+ω i2 t 2 (n)+...ω ik t 2 (n)+...+ω iN t N (n) , it can be seen that the change of normal nodes is related to the time state of other nodes at the previous moment. It has been proved that if there are no bad points in the network, after n iterations through the above model, the network can converge, that is, the node state value can be reached Synchronization, expressed as t by the formula 1 (n+1)=t 2 (n+1)=…=t N (n+1).

[0040] But if the network has a bad point, here it is assumed to be k, then the time of node k is in an uncontrollable state, which is a disordered value, that is, t k (n)=σ(n), σ(n) obeys an unspecific noise distribution, so bad points cannot use the iterative formula of the normal nodes above. It can be seen from here that the state change of the node with only bad points has nothing to do with other n...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an identification method for anomalous points of cooperative synchronization in a distributed network. The identification method for the anomalous points of cooperative synchronization in the distributed network includes: obtaining complete local information by using a small amount of information which is related to positioning and contained in each node and communication of the anomalous points and adjacent nodes, and then using local area network information to estimate the position of a bad point. The identification method for the anomalous points of cooperative synchronization in the distributed network avoids dependence on a reference node in a traditional centralization positioning method, and achieves quick positioning of the anomalous points in a wireless sensor network. The identification method for the anomalous points of cooperative synchronization in the distributed network uses two different correlation coefficient computing methods to perform correlation analysis on the whole network, can obtain the result that which node is the bad point only through a final correlation matrix, and achieves the purpose of quickly positioning the bad point in the distributed network well, and furthermore accuracy rate of the quick positioning reach up to a value above 95%.

Description

technical field [0001] The invention relates to the field of wireless sensor networks, in particular to a method for identifying synchronous abnormal points in a distributed network. Background technique [0002] Wireless sensor network is a new information acquisition and processing technology, which provides people with a new effective way to acquire and process information. It is a special wireless self-organizing network (Ad Hoc Networks) composed of a large number of sensor nodes. It is a low-cost, low-power, multi-functional wireless sensor device. Its appearance has changed the interaction between humans and the physical world In this way, the integration of the physical world and the information world becomes possible. Wireless sensor nodes can detect useful information including temperature, humidity, light, object size, moving speed and direction in real time without being restricted by time, place and environment. The cost of wireless sensor network nodes is low...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04W24/00H04W64/00H04W84/18
Inventor 杨琦钱静丰林啸
Owner XIAMEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products