Network performance oriented study of sensor nodes combining improved COOT and MOAHA algorithms

Zhiliang Xiao; Ying Chen; Nan Yang

doi:10.1117/12.3026737

9 February 2024 Network performance oriented study of sensor nodes combining improved COOT and MOAHA algorithms

Zhiliang Xiao, Ying Chen, Nan Yang

Proceedings Volume 13073, Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023); 130730M (2024) https://doi.org/10.1117/12.3026737
Event: Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023), 2023, Changsha, China

Abstract

Wireless Sensor Network (WSN) plays a vital role in the field of information technology. Sensor nodes, as the core components of the network, are responsible for sensing and collecting data in the environment and transmitting them to other nodes or a central server through the network. To increase the coverage effect and connectivity of network nodes, the study combines the Coot Bird Swarm Optimization Algorithm (COOT) with the Multi-Objective Artificial Hummingbird Algorithm (MOAHA) were combined and improved using a multi-strategy approach. The results show that the average coverage of the improved White Bone Top Bird Flock Optimization Algorithm is 97.48%, and the difference between the improved Multi-Objective Artificial Hummingbird Algorithm on the functions F1 and F2, respectively, is 0.8916 and 0.0092. Therefore, the research of sensor nodes oriented to the performance of the network effectively improves the performance of optimal coverage of the sensor nodes of the WSNs and provides the multi-objective node deployment scheme problem.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhiliang Xiao, Ying Chen, and Nan Yang "Network performance oriented study of sensor nodes combining improved COOT and MOAHA algorithms", Proc. SPIE 13073, Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023), 130730M (9 February 2024); https://doi.org/10.1117/12.3026737

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