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Wireless sensor network data fusion method based on auto-encoder and network system

A wireless sensor and network data technology, applied in the field of communication, can solve problems such as uneven energy consumption and shortened network life cycle

Active Publication Date: 2021-02-12
INNER MONGOLIA UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the technical problems of the existing APTEEN routing protocol, such as uneven energy consumption and premature death of some nodes, resulting in shortened network life cycle, the present invention provides a wireless sensor network data fusion method and network system based on an autoencoder

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  • Wireless sensor network data fusion method based on auto-encoder and network system
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  • Wireless sensor network data fusion method based on auto-encoder and network system

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Embodiment 1

[0066] see figure 1 , this embodiment provides an autoencoder-based wireless sensor network data fusion method, the data fusion method is actually an adaptive periodic threshold-sensitive energy-efficient algorithm (SAE-APTEEN) based on a deep autoencoder. The data fusion method optimizes the data fusion of APTEEN by using the deep self-encoder adapted to the wireless sensor network, and then considers the remaining energy of the node, the distance between the base station and the node density, and improves the APTEEN cluster head distribution problem for the APTEEN protocol. Protocol cluster head election threshold formula. Wherein, the data fusion method includes the following steps, namely steps (1)-(8).

[0067] (1) First determine the remaining energy factor, the distance factor between the node and the base station, and the node density factor, and then add the remaining energy factor, distance factor, and node density factor to the cluster head election threshold formu...

Embodiment 2

[0105] This embodiment provides a wireless sensor network data fusion method based on an autoencoder. The method is simulated and verified on the basis of Embodiment 1, and a specific implementation manner is provided. Among them, the performance of SAE-APTEEN is verified on the MATLAB simulation platform. The topological range of the wireless sensor network is 200m*200m, and 200 sensor nodes are randomly distributed. The position of the base station is fixed, and the coordinates are (100m, 100m). The initial energy of any node is 0.5J, HT is 1, ST is 0.1, and the counting time is 100s. APTEEN data fusion rate is 0.6. The size of the data packet is 4000bit, and the size of the cluster node information table is 200bit. The expression of node consumption model in wireless sensor network is:

[0106]

[0107] E. Rx (k)=E Rx-elec (k)=E elec *k

[0108] In the formula, E elec E Tx (k,d) is the energy consumption of the sending node, E Rx (k) The consumed energy of the r...

Embodiment 3

[0117] This embodiment provides a data fusion network system for a cognitive wireless sensor network based on a deep autoencoder, the system applies the data fusion method for a wireless sensor network based on an autoencoder in Embodiment 1 or 2, and includes a cluster head Election threshold formula improvement module, training module, cluster head election module, data transmission module, cluster node information table transmission module, encoder parameter transmission module, data fusion module, fusion compression data transmission module and reconstruction judgment module.

[0118] The cluster head election threshold formula improvement module is used to first determine the remaining energy factor, the distance factor between the node and the base station, and the node density factor, and then add the remaining energy factor, distance factor, and node density factor to the cluster head election threshold formula of the wireless sensor network To improve the cluster head ...

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Abstract

The invention discloses a wireless sensor network data fusion method based on an auto-encoder and a network system. The method comprises the following steps: adding a residual energy factor, a distance factor and a node density factor into a cluster head election threshold formula for improvement; training the stacked auto-encoder at the base station to obtain encoder parameters; cluster head election being carried out according to an improved cluster head election threshold formula; the cluster member node transmitting the node data to the cluster head; the cluster head sending the cluster node information table to the base station; the base station sending the encoder parameters to the corresponding cluster heads; the cluster head fusing the node data according to encoder parameters; thecluster head transmitting the fused compressed data to a base station; and reconstructing base station data, judging whether all nodes die or not, if so, ending, and otherwise, executing a cluster head election step. According to the invention, the energy loss caused by sending redundant data is reduced, so that the number of dead nodes and the node death speed are reduced, the network energy consumption is reduced and balanced, the network life cycle is prolonged, and the data transmission efficiency is improved.

Description

technical field [0001] The present invention relates to a data fusion method in the field of communication technology, in particular to a data fusion method for a wireless sensor network based on an autoencoder, and also relates to a data fusion network system for a cognitive wireless sensor network based on a deep autoencoder. Background technique [0002] As a distributed sensor network, wireless sensor network can be widely used in military, intelligent transportation, environmental monitoring, medical and health and other fields. The wireless sensor network is mainly controlled by the routing protocol, and the quality of the network performance is largely determined by the routing protocol. The clustering routing protocol has the advantages of convenient topology management, high energy utilization rate, and is conducive to data fusion and transmission processing. [0003] APTEEN (Adaptive Threshold-sensitive Energy Efficient Sensor Network Protocol) is a typical cluste...

Claims

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Application Information

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IPC IPC(8): H04W24/02H04W28/02H04W28/06H04W40/10H04W40/32H04W84/18
CPCH04W24/02H04W28/0226H04W28/06H04W40/10H04W40/32H04W84/18Y02D30/70
Inventor 王树彬宋昱
Owner INNER MONGOLIA UNIVERSITY
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