Computer Science ›› 2024, Vol. 51 ›› Issue (6): 375-383.doi: 10.11896/jsjkx.230300130

• Computer Network • Previous Articles     Next Articles

Enhanced Snake Optimizer Based RFID Network Planning

LI Zhiqian, ZHENG Jiali, CHEN Yijun, ZHANG Jiangbo   

  1. School of Computer,Electrics and Information,Guangxi University,Nanning 530004,China
    Guangxi Key Laboratory of Multimedia Communications and Network Technology,Nanning 530004,China
  • Received:2023-03-16 Revised:2023-06-28 Online:2024-06-15 Published:2024-06-05
  • About author:LI Zhiqian,born in 1996,postgraduate.Her main research interests include RFID network planning and so on.
    ZHENG Jiali,born in 1979,professor.His main research interests include Internet of Things,RFID and AI.
  • Supported by:
    National Natural Science Foundation of China(62366004).

Abstract: Aiming at the optimal deployment of radio frequency identification(RFID) network planning,an enhanced snake optimizer based on the embedded sine cosine algorithm(SCA) and adaptive threshold is proposed.In the population initialization stage,taking advantage of the uniformity and ergodicity of the Circle chaotic map,the algorithm mechanisms such as sine cosine algorithm and adaptive threshold are introduced in the local search stage and the development stage,respectively,to get rid of the disadvantages of the snake optimizer such as uneven initialization process,easy to fall into local optimization and slow convergence speed.On the basis of meeting the four objectives of 100% label coverage,reducing the collision interference between readers and writers,achieving the load balance of readers and writers,and reducing the total transmission power,the optimal deployment location of readers is solved.Enhanced snake optimizer(ESO) is compared with particle swarm optimization(PSO),grey wolf optimizer(GWO),and salp swarm algorithm(SSA).Experimental results show that enhanced snake optimizer has a stronger ability to optimize the deployment of RFID network,and its overall performance is significantly improved.Under the same experimental conditions,the optimal fitness value of ESO is 28.1% higher than PSO,17.7% higher than GWO,and 22.9% higher than SSA,which can more effectively obtain the optimal RFID network planning and deployment scheme.

Key words: RFID network, Snake optimizer, Circle chaotic map, Sine-Cosine algorithm, Adaptive threshold, Network planning

CLC Number: 

  • TP301.6
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