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Optimization method of radio frequency identification network layout based on multi-population symbiotic evolution

A radio frequency identification and network layout technology, applied in the network field, can solve problems such as poor stability, slow convergence speed, and inability to obtain network layout solutions, and achieve the effects of high stability, fast convergence speed, and small population size.

Active Publication Date: 2017-06-13
XIDIAN UNIV
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Problems solved by technology

Therefore, using the genetic algorithm to solve the RFID network layout problem cannot imitate the intelligence of biological processing things very well. In addition, the genetic algorithm has the disadvantages of premature convergence, slow convergence speed, poor stability, etc., so that a good network layout scheme cannot be obtained.

Method used

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  • Optimization method of radio frequency identification network layout based on multi-population symbiotic evolution
  • Optimization method of radio frequency identification network layout based on multi-population symbiotic evolution
  • Optimization method of radio frequency identification network layout based on multi-population symbiotic evolution

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Embodiment Construction

[0026] Such as figure 2 As shown, the radio frequency identification RFID network model is mainly composed of tags and readers. The communication between the tags and the readers is realized through electromagnetic waves. The readers emit energy signals, and the signals are transmitted through the antennas of the readers. The tags complete the process through their own antennas. Receive function.

[0027] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0028] Step 1. Set the parameter Network Parameters.

[0029] Set the following parameters according to the radio frequency identification network model:

[0030] The wavelength of the electromagnetic wave λ=0.328m, the threshold power R of the reader and the tag communication q =-14dBm, reader antenna gain G 1 =6.7dBi; tag antenna gain G 2 = 3.7dBi.

[0031] Step 2. Set the parameters of the multi-population symbiotic evolutionary algorithm.

[0032] In the field of func...

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Abstract

The invention discloses a radio frequency identification network layout optimization method based on multi-population symbiotic evolution, which mainly solves the problems of prematurity, slow convergence speed and poor stability in the prior art when using a genetic algorithm to lay out a network. Its technical scheme is: its implementation steps are: 1. Randomly group the population, independently calculate the fitness of each sub-population objective function, and design a strategy for sequentially comparing the objective function and a tentative deletion operator; 2. In the iterative process, Share the global best value found by the entire population so far; 3. Each sub-population updates its own position of each sub-population according to the global optimal position, so as to find the best network layout scheme. The invention has the advantages of small initial population size, fast convergence speed and high stability, and can effectively solve the problem of network layout.

Description

technical field [0001] The invention belongs to the field of network technology, and in particular relates to a radio frequency identification network layout optimization method, which can be used for network planning. Background technique [0002] In recent years, radio frequency identification (RFID) technology, as a representative of the Internet of Things technology, has attracted more and more attention from researchers. Many aspects of technical issues are also involved in the RFID system. For example, with the development and wide application of RFID technology, the layout optimization of RFID network has become a sharply challenging task. For the RFID network layout optimization problem, there are many constraints and objectives involved, and it has been proved to be an NP-hard problem. The purpose of the RFID network layout optimization problem is to find the best position of the reader under certain constraints, such as tag coverage, number of readers, and interfe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K17/00
Inventor 刘静焦李成李禹龙马文萍马晶晶
Owner XIDIAN UNIV
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