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RFID Network Layout Method Based on Load Balance and Particle Swarm Algorithm

A particle swarm algorithm and load balancing technology, applied in the network field, can solve the problems of unavailable network layout scheme, slow convergence speed, poor stability, etc., and achieve the effect of small population size, fast convergence speed and high stability

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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  • RFID Network Layout Method Based on Load Balance and Particle Swarm Algorithm
  • RFID Network Layout Method Based on Load Balance and Particle Swarm Algorithm
  • RFID Network Layout Method Based on Load Balance and Particle Swarm Algorithm

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Embodiment Construction

[0025] 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.

[0026] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0027] Step 1. Set the parameter Network Parameters.

[0028] Set the following parameters according to the radio frequency identification network model:

[0029] 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.

[0030] Step 2. Set the parameters of the particle swarm evolution algorithm.

[0031] In the field of function optimizati...

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Abstract

The invention discloses a radio frequency recognition network layout method based on load balance and particle swarm optimization, and mainly aims to solve the problems that in the prior art a genetic algorithm layout network is easy to be premature in advance, slow in convergence rate and poor in stability. According to the technical scheme, the method comprises the following steps: 1, performing initial encoding on particle swarm individuals; 2, calculating the fitness value of each individual in the particle swarm; 3, comparing the fitness value of each individual, and calculating an overall optimal individual; 4, updating the position information of each individual in the particle swarm by using a particle swarm optimization method; 5, judging whether a terminating condition is met or not, if the terminal condition is met, performing exploratory delete calculation, and outputting an optimal individual, and if not returning to step 2. The radio frequency recognition network layout method has the advantages of small initial group scale, rapid convergence speed and high stability, and the radio frequency recognition layout problem can be effectively solved.

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 location of the readers under certain constraints, such as tag coverage, number of readers, interferen...

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刘红英熊涛
Owner XIDIAN UNIV
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