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Multi-population symbiotic evolution based radio frequency identification network layout optimization method

A radio frequency identification and network layout technology, applied in the network field, can solve the problems of slow convergence speed, unable to obtain network layout plan, poor stability, etc., and achieve the effect of fast convergence speed, small population size and high stability

Active Publication Date: 2015-04-08
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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  • Multi-population symbiotic evolution based radio frequency identification network layout optimization method
  • Multi-population symbiotic evolution based radio frequency identification network layout optimization method
  • Multi-population symbiotic evolution based radio frequency identification network layout optimization method

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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 multi-population symbiotic evolution based radio frequency identification network layout optimization method, and mainly solves the problems of proneness to precocity, slow convergence and poor stability due to the fact that the genetic algorithm is used for network layout in the prior art. The method includes the implementation steps: firstly, randomly grouping populations, independently calculating fitness of each sub-population objective function, designing and sequentially comparing strategies of the objective functions and deleting operators tentatively; secondly, in the process of iteration, sharing the whole population till now, and finding out the global best fitness; thirdly, updating the own position of each sub-population according to the global optimal position for each sub-population so as to find out the optimal network layout scheme. The method has the advantages of small initial population size, fast convergence and high stability, and the problem about network layout can be solved effectively.

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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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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