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Research on Wireless Sensor Network Coverage Path Optimization Based on Biogeography-Based Optimization Algorithm
Author(s) -
Guojun Chen,
Xiangdong Qin,
Ningsheng Fang,
Wenbo Xu
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/7826132
Subject(s) - computer science , wireless sensor network , path (computing) , software deployment , particle swarm optimization , genetic algorithm , algorithm , population , distributed computing , real time computing , computer network , machine learning , demography , sociology , operating system
Path selection is one of the key technologies of wireless sensor network (WSN). A reasonable choice of coverage path can improve the service quality of WSN and extend the life cycle of WSN. Biogeography-based optimization (BBO) is widely used in the field of cluster intelligent optimization because its search method has a better incentive mechanism for population evolution. In this paper, the move-in and move-out operation and mutation operation of the BBO algorithm enable WSN to find an efficient routing path. In this paper, simulation experiments are carried out in two scenarios of regular deployment and random deployment of WSN nodes. The experimental results show that the quality of the WSN coverage path solution optimized by the BBO algorithm in the two scenarios is better than that of the particle swarm algorithm and genetic algorithm.

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