Abstract:  In order to rationally deploy the wireless sensor network nodes and reduce the coverage area of the
target area, an optimization scheme based on the optimal global artificial bee colony algorithm is proposed. The
improved algorithm introduces the selection mechanism to distinguish the honey sources. The better ones learn
from the differential evolution strategy to search neighborhood, and the inferior ones use the global guidance
mechanism to optimize nectar. It will improve the iterative efficiency, convergence speed and global search
ability. This algorithm is applied to the WSN(Wireless Sensor Network) node distribution optimization problem,
and compared with the optimization results of artificial bee colony algorithm and global artificial bee colony
algorithm. The simulation results show that the average coverage is at least 1% higher and the worst coverage is
at least 2% higher than the two algorithms. It can be seen that the coverage optimization of the target area based
on this algorithm is superior to the other two algorithms, which effectively improves the perceived performance
of WSN.

Key words: node distribution, preferred mechanism, coverage rate, differential evolution,  wireless sensor network (WSN), artificial bee colony algorithm, global guiding mechanism, convergence speed