Network data compressing method, network system and synthesis center equipment

A compression method and network data technology, applied in the transmission system, network topology, electrical components, etc., can solve the problem that the data compression method cannot be applied to the wireless distributed sensor network, and achieve the effect of meeting efficiency and accuracy and avoiding bandwidth

Inactive Publication Date: 2010-01-06
BEIHANG UNIV
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Problems solved by technology

However, the data compression method for a single sensor cannot be applied

Method used

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  • Network data compressing method, network system and synthesis center equipment
  • Network data compressing method, network system and synthesis center equipment
  • Network data compressing method, network system and synthesis center equipment

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Embodiment Construction

[0026] The technical solutions of the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0027] Embodiment 1 of the present invention provides a method for compressing network data, which is used to solve the problem that the information of multiple nodes can be jointly compressed only by calculating the correlation between nodes in the network.

[0028] figure 1 It is a flowchart of a method for compressing network data in Embodiment 1 of the present invention, such as figure 1 As shown, the network data compression method of the present embodiment includes the following steps:

[0029] Step 100. In a sensor network including J network nodes, obtain the node data of the J network nodes by sampling, wherein the node data of the J network nodes are correlated, and the node data of each network node have a common component and a special component with sparsity under the sam...

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Abstract

The invention provides a network data compressing method, a network system and synthesis center equipment. The method comprises the steps: sampling in a sensor network comprising J network nodes and obtaining node data of the J network nodes, wherein the node data of the J network nodes are relevant, and the node data of each network node have a pubic component and a special component with sparseness under a same base; carrying out compression processing on the node data of each network node in the sensor network by applying a random compression matrix, obtaining node compression data corresponding to the network node, wherein the random compression matrix is generated by a physical address of the network node; and sending the node compression data in each network node in the sensor network and the physical address corresponding to the node compression data to the synthesis center equipment. The invention can effectively and jointly compress the information of a plurality of nodes, avoid that node compunction takes up high bandwidth while calculating the relativity and satisfy the double requirements on efficiency and precision.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of wireless networks, and in particular to a method for compressing network data, a network system and a fusion center device. Background technique [0002] Future monitoring and listening systems will rely on a variety of distributed wireless sensor networks to ensure reliable data acquisition in extremely complex and unstable environments. The existing detection system uses information collected by each node in the network to be transmitted and then fused at the destination node for detection. This type of monitoring system has been widely used in military and remote sensing, including control, communication, intelligent monitoring, tracking and identification. Non-military fields such as navigation, meteorology, air traffic management, and medical treatment. Due to bandwidth and energy constraints, efficient data compression and reconstruction become very important. Therefore, ...

Claims

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Application Information

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IPC IPC(8): H04L29/06H04W84/18
Inventor 张军杜冰郑磊
Owner BEIHANG UNIV
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