Research On Multi-objective Cloud Workflow Task Scheduling Mechanism Based On Bee Colony And Gentic Hybird Algorithm

As more and more scientific workflow applications begin to be deployed in the IaaS cloud environment,how to effectively schedule workflow tasks in different types of virtual machine instances has become a research hotspot.The workflow scheduling problem in the cloud environment is a well-known NP-hard problem.In view of this,this paper designs and implements a multi-objective workflow task scheduling mechanism based on bee colony and genetic hybrid algorithm to minimize the total completion time and total execution cost of the workflow.Specifically,the main research contents are as follows:1.The multi-objective mathematical optimization model of workflow scheduling problem in IaaS environment is constructed.The heterogeneity and availability of virtual machine instances in IaaS platform are considered comprehensively,and the makespan and cost of workflow are optimized.2.A hybrid algorithm based on genetic algorithm and bee colony algorithm is designed and implemented to solve the multi-objective optimization problem.The hybrid algorithm combines the advantages of the bee colony and the genetic algorithm to speed up the evolution of the population,thereby improving the convergence speed and accuracy of the algorithm.3.The performance of the proposed HGAABC algorithm is evaluated by simulation experiments.The experimental results show that compared with other advanced algorithms,the HGAABC algorithm proposed in this paper can obtain a better compromise solution,effectively reducing the makespan and cost of the workflow.