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A technology of differential evolution and node positioning, which is applied in the direction of location information-based services, network planning, electrical components, etc., and can solve the problem of low positioning accuracy
Active Publication Date: 2021-09-07
SUN YAT SEN UNIV
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[0026] In order to solve the problem of the existence of anisotropic factors in the wireless sensor network and the inherent defects in the current positioning algorithm, which leads to low positioning accuracy, the present invention provides a The differential evolution node positioning method based on polynomial approximation, which introduces weights for different anchor nodes, makes its importance in the calculation of unknown node coordinates more reasonable, and then realizes precise positioning under different networks
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Embodiment 1
[0098] Such as figure 1 As shown, a polynomial approximation differential evolution node location method (expressed in English as: proposed), this method under the condition that there are several anchor nodes with known positions in the wireless sensor network, by using the connectivity relationship between different anchor nodes , which is the hop count of the shortest route path between nodes, to realize unknown node location.
[0099] The described node positioning method comprises the steps as follows:
[0100] S1: Through the anchor node flooding information, all anchor nodes in the network obtain the hop count and location information of the anchor node;
[0101] S2: Calculate the optimal number of hops between anchor nodes according to the obtained position information of the anchor nodes;
[0102] S3: Calculate the hop adjustment factor of each anchor node according to the optimal hop number between anchor nodes;
[0103] S4: Use the hop adjustment factor of the an...
Embodiment 2
[0194] A computer system includes a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, the steps of the method are as follows:
[0195] S1: Through the anchor node flooding information, all anchor nodes in the network obtain the hop count and location information of the anchor node;
[0196] S2: Calculate the optimal number of hops between anchor nodes according to the obtained position information of the anchor nodes;
[0197] S3: Calculate the hop adjustment factor of each anchor node according to the optimal hop number between anchor nodes;
[0198] S4: Use the hop adjustment factor of the anchor node to correct the hop number from the unknown node to the anchor node;
[0199] S5: The unknown node estimates the distance between itself and the anchor node through polynomial approximation, and obtains the estimated distance;
[0200]S6: The unknown node constructs the objective fu...
Embodiment 3
[0202] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method steps implemented are as follows:
[0203] S1: Through the anchor node flooding information, all anchor nodes in the network obtain the hop count and location information of the anchor node;
[0204] S2: Calculate the optimal number of hops between anchor nodes according to the obtained position information of the anchor nodes;
[0205] S3: Calculate the hop adjustment factor of each anchor node according to the optimal hop number between anchor nodes;
[0206] S4: Use the hop adjustment factor of the anchor node to correct the hop number from the unknown node to the anchor node;
[0207] S5: The unknown node estimates the distance between itself and the anchor node through polynomial approximation, and obtains the estimated distance;
[0208] S6: The unknown node constructs the objective function according to the coordinates ...
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Abstract
The invention provides a polynomial approximation differential evolution node positioning method. The method comprises the following steps of: S1, enabling all anchor nodes in a network to obtain hop counts and position information of the anchor nodes through flooding information of the anchor nodes; S2, calculating the optimal hop count among the anchor nodes according to the obtained position information of the anchor nodes; S3, calculating a hop count adjustment factor of each anchor node according to the optimal hop count between the anchor nodes; S4, correcting the hop count from the unknown node to the anchor node by using the hop count adjustment factor of the anchor node; S5, estimating the distance between the unknown node and the anchor node through polynomial approximation by the unknown node to obtain an estimated distance; and S6, enabling the unknown node to construct a target function according to the coordinates of the anchor node and the estimated distance, and obtaining a solution corresponding to the minimum value of the target function through differential evolution to serve as the coordinates of the unknown node, so that the positioning of the unknown node is realized. According to the method, the weights are introduced to different anchor nodes, so that the importance degree of the anchor nodes in unknown node coordinate calculation is more reasonable, and accurate positioning under different networks is further realized.
Description
technical field [0001] The present invention relates to the technical field of wireless sensor networks, and more specifically, to a polynomial approximation differential evolution node positioning method. Background technique [0002] Wireless sensor networks (WSNs) are known as one of the 21 most influential technologies in this century, and belong to the interdisciplinary frontier fields of computer, communication and mathematics. It is a self-organizing data processing network formed by multiple sensor nodes with certain functions arranged in the monitoring area through data collection and data transmission. Through the dense deployment of sensor nodes in the network, data collection and quantification, data aggregation and data transmission operations can be realized. As a modern intelligent network, wireless sensor networks have been widely used in military, Internet of Things, environmental monitoring, modern transportation (such as shared bicycles in the past two ye...
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