Affiliations: [a] College of Education, Shanghai Normal University, Shanghai, China
| [b] School of Basic Medical Sciences, Guangxi Medical University, Nanning, China
| [c] Department of Physics and Engineering Technology, Guilin Normal College, Guilin, China
Correspondence:
[*]
Corresponding author. Ying Hou, Department of Physics and Engineering Technology, Guilin Normal College, Guilin, China. E-mail: houying_glnu@163.com.
Abstract: When studying the application of discrete fruit fly algorithm in enhancement of wireless sensor node coverage, the wireless sensor node coverage model is designed according to the node measurement model, and the discrete fruit fly algorithm is used to evaluate each initial population in the wireless sensor node coverage to determine the elite individuals. The number of retentions of the elite individual is calculated in the essence library, and the final result is output when the number of retentions of the elite individual is greater than the minimum number of retentions of the elite individual. Conversely, inter-population immigrations are implemented to form new fruit fly populations. The classification olfactory random search method based on adaptive compensation is adopted in the population. The fruit fly individuals are evaluated by the taste judgment function, and they are visually located to re-determine the optimal individuals of each population. The above steps are repeated until the number of retentions of elite individuals is greater than the minimum number of retentions of elite individuals. Then the optimal solution of the wireless sensor node coverage model is output, and the optimization scheme of the wireless sensor node coverage is designed according to the optimal solution. The experimental analysis shows that when the number of iterations is 50, the maximum node coverage and node fitness are 99.81% and 0.99 respectively. When the number of nodes is 20, the time of the enhanced node is the shortest, 9.8 ms. That is, the method can significantly enhance the node coverage effect.
