Research on Cloud Computing Task Scheduling Based on Mixed Strategy Whale Optimization Algorithm
A cloud computing task scheduling method based on the Hybrid Strategy Whale Optimization Algorithm(MSWOA)is proposed to address issues such as long task execution time,high system execution costs,and imbalanced system loads in the process of cloud computing task scheduling.Firstly,use Tent chaotic mapping to initialize the whale population to enhance population diversity and make the distribution of whale individuals more uniform;Then,an adaptive probability threshold was proposed to balance the global search capability and local de-velopment capability of the algorithm,and the Levy flight strategy was introduced in the random search stage of the algorithm to expand the search space and search capability of the algorithm;Finally,a multi-objective fitness function was designed for the task scheduling process,and an algorithm was used to solve the multi-objective task scheduling problem in cloud computing.The simulation experiment of MSWOA was conducted using CloudSim cloud computing simulation software,and the results of comparing MSWOA with NOA,ZOA,OAWOA,and TSWOA algorithms showed that compared with other algorithms,MSWOA achieved better performance at different task scales.It not only re-duced the maximum completion time and system execution cost of tasks,but also improved the average load rate of the system,which has sig-nificant advantages in multi-objective task scheduling in cloud computing.
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