
Optimization of Relay Node Deployment in Wireless Sensor Communication Networks Based on IGA-RNDP Algorithm
Author(s) -
Shubo Xu,
Cheng Zhong
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3596296
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Reasonably deploying wireless sensor communication network relay nodes can not only expand network coverage and ensure that signals can span longer distances, but also enhance signal strength and reduce loss and errors during data transmission. To achieve reasonable deployment of relay nodes, a relay node deployment algorithm on the basis of improved genetic algorithm is proposed. By adjusting the operation method of traditional genetic algorithms and introducing relevant algorithm optimization mechanisms, the research method can effectively handle the deployment of relay nodes. This algorithm was compared with four other algorithms in the deployment of relay nodes in real traffic datasets to prove the effectiveness. The method had a maximum fitness value of 0.98 in the testing set and required 48 iterations to achieve convergence. When the communication radius of the sensor node was 20m, the coverage rate for different numbers of sensors was 100%. The average number of deployed nodes was 154.38, which was better than other methods. When the communication radius was 40m, the coverage redundancy always remained at a low level. The solution time for the problem model was within 2 seconds. In large-scale network environments, the research method deployed the fewest number of relay nodes and had a concentrated distribution, with statistically significant differences compared to other algorithms. The research method could achieve 100% coverage and low coverage redundancy with fewer relay nodes in a shorter period of time. The statistically significant differences existed between the research method and other algorithms.
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