Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (9): 2668-2675.doi: 10.13229/j.cnki.jdxbgxb.20221436

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Link quality optimization based data transmission algorithm for wireless sensor network

Jian-po LI1(),Kun LIU1,Wei-hua ZHU2   

  1. 1.School of Computer Science,Northeast Electric Power University,Jilin 132012,China
    2.School of Software Engineering,Jilin Technology College of Electronic Information,Jilin 132021,China
  • Received:2022-11-12 Online:2024-09-01 Published:2024-10-29

Abstract:

To improve transmission rates in wireless sensor network and solve problems of interference, data anomalies, collision and congestion during clustered routing, a data transmission algorithm was proposed to optimize link quality. Applying cross layer design, introducing physical layer channel information, and reducing interference between clusters during data collection through random frequency hopping of each cluster. The priority of unusual data was defined to optimize slot allocation within clusters. With the access control in MAC layer, factors affecting inter-cluster transmission was considered and a competitive scheme was developed to avoid conflicts when multiple nodes access cluster heads. It compared data queues of accessing cluster heads and pre-reserved queues of receiving cluster heads to detect congestion. And the original routing was changed to solve congestion. Experimental results show that compared to LEACH, UCDTS and FPCRA algorithms, it effectively improves the data transmission quantity, the network life cycle and other indicators.

Key words: communication and information system, wireless sensor network, cross-layer design, random frequency hopping, conflict avoidance, pre-reserved queue

CLC Number: 

  • TN92

Fig.1

Diagram of interference between neighbor clusters"

Fig.2

Diagram of conflicts between intra-cluster collection and inter-cluster transmission"

Fig.3

Competitive forwarding routing between clusters in case of heavy data conflicts"

Fig.4

Data frame structure of congestion notification"

Fig.5

Comparison of the percentage of nodes currently alive in the network"

Fig.6

Comparison of the number of packets successfully sent"

Fig.7

Comparison of overall energy consumption percentage in the network"

Fig.8

Comprehensive performance comparison of LQOTA and other algorithms"

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