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WSN node locating method based on heterogeneous double-population particle swarm optimization

A technology of particle swarm optimization and node positioning, applied in electrical components, wireless communication, network topology, etc., can solve problems such as slow convergence speed, large positioning error, and easy to fall into local optimum

Inactive Publication Date: 2014-01-15
JIANGXI UNIV OF SCI & TECH
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Problems solved by technology

[0005] In order to solve the technical problems that the existing wireless sensor network node positioning methods based on group particle optimization often have slow convergence speed, poor real-time performance, easy to fall into local optimum, and large positioning errors, the present invention proposes a method based on different WSN node location method based on mass dual population particle swarm optimization

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  • WSN node locating method based on heterogeneous double-population particle swarm optimization
  • WSN node locating method based on heterogeneous double-population particle swarm optimization
  • WSN node locating method based on heterogeneous double-population particle swarm optimization

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[0093] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0094] This embodiment is based on figure 1 The practical engineering problem of wireless sensor network node localization shown in figure 1 Among them, 12 squares represent 12 anchor nodes, and 50 circles represent 50 unknown sensor nodes. The specific implementation steps of the present invention are as follows:

[0095] Step 1, user-defined initialization parameters, the initialization parameters include the number of anchor nodes K=12, K anchor node position vector Z:

[0096] Z=[20.00, 11.77, 20.72, 28.33, 92.14, 25.73, 45.67, 92.84, 70.01, 45.00, 91.43, 42.42, 53.33, 42.46, 19.36, 31.67, 61.72, 6.83, 70.00, 115.434, 82.8 , 86.67, 98.89, 53.87, 95.00, 26.59, 25.19, 103.33, 32.09, 64.20, 116.66, 94.08, 47.37]

[0097] The position of the jth anchor node is (Z j×3-2 ,Z j×3-1 ,Z j×3 ), the number of unknown se...

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Abstract

The invention discloses a WSN node locating method based on heterogeneous double-population particle swarm optimization. According to the method, community self-adaptation activity behavior of animals in the nature is merged in a particle swarm optimization algorithm, a fitness function is designed based on the distance between an anchor node and an unknown sensor node, two heterogeneous child populations are used for maintaining good variety by simulating the community activity mode of the animals in the nature, a composite reverse learning strategy and an elite chaos search strategy are merged in the two child populations respectively by simulating the natural law that the animals in different communities in the nature have different preferences and habits, different search modes are carried out on the two child populations, advantage complement of various search modes is achieved, so that global searching ability is enhanced, and locating accuracy is improved. Meanwhile, communicating behavior of the animals in different communities in the nature is simulated, in appointed evolution generations at intervals, individuals are exchanged between the two child populations, sharing of high-quality search information and a guiding effect are achieved, and accordingly convergence speed is improved, and locating real-time performance is improved.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor networks, and relates to a WSN (wireless sensor network) node positioning method based on heterogeneous dual-population particle swarm optimization. Background technique [0002] The wireless sensor network realizes the organic fusion between the physical world, the computer world and the ternary world of human society, and is the peripheral nerve of today's Internet of Things. Because of its very broad practical application prospects, it has attracted great attention from academia and industry, and is considered to be one of the most influential technologies in the 21st century. In wireless sensor network applications, the positioning of wireless sensor network nodes is the core supporting technology, which is a complex optimization problem. The swarm particle optimization algorithm is an effective modern intelligent optimization algorithm that simulates the behavior of natural animal gr...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00H04W84/18
Inventor 郭肇禄岳雪芝刘建生熊小峰刘松华张克俊谢大同
Owner JIANGXI UNIV OF SCI & TECH
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