Optimization Scheduling of Cloud Service Resources Based on Beetle Antennae Search Algorithm

As cloud computing systems have the characteristics of a large number of users, large task scales, and distributed storage of massive data, reasonable scheduling system resources has become a difficult problem in cloud computing research, and it is particularly important to design an efficient cloud computing task scheduling algorithm. Although most traditional optimization algorithms can achieve better results in cloud resource scheduling problems, there is still much room for improvement. On the basis of summarizing the existing research work, this paper aims at optimizing task execution time and algorithm execution efficiency, and proposes a cloud resource scheduling optimization strategy based on the Beetle Antennae Search (BAS). This article first analyzes the principle of BAS algorithm and discusses its mathematical model. Secondly, the application of BAS algorithm in cloud computing resource scheduling problem is analyzed, fitness calculation function is designed, and individual coding schemes are studied. Finally, in order to verify the effectiveness of the scheduling strategy, experiments were conducted on the optimization effect of the algorithm by building a CloudSim cloud computing simulation platform. The experimental results show that the BAS algorithm has a better optimization effect than the PSO algorithm, and can significantly reduce the iteration time of the algorithm.