Application of Bayesian predictive bee colony algorithm in WSN optimization
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Abstract:
The node distribution of wireless sensor network(WSN) is often unreasonable, and always has many monitoring blind spots.Aiming at this problem,Bayesian predictive artificial bee colony algorithm (BPABC) is proposed to develop a node distribution scheme. Based on the idea of Bayesian prediction algorithm, this algorithm predicts the probability of optimal solution of each nectar source in the bee colony algorithm, and guides the followed bees to seek optimal solution. A designed algorithm is used to optimize the distribution of nodes in WSN, and the effect is compared with those of artificial bee colony algorithm and global artificial bee colony algorithm. The results show that BPABC is superior to the other two algorithms in terms of average coverage and worst coverage. Besides,this algorithm also has obvious advantages in iterative convergence rate. In order to further verify the practicability of the improved algorithm, this paper uses BPABC algorithm to develop WSN node distribution scheme for different monitoring areas. Coverage for all WSNs is around 97% with a standard deviation no more than 0.005% can be seen that the WSN node distribution optimization scheme based on BPABC has high coverage,good adaptability and stability.
