Research On Task Scheduling Based On Sharing Mechanism And Swarm Intelligence Optimization Algorithm In Cloud Computing

Since twenty-first Century,"cloud computing" has triggered waves of IT,enterprise and academic researchers' application and research,and has been rapidly applied to all walks of life.The cloud computing platform is a very large and heterogeneous computing platform;its computing power and speed depends on the hardware of the processor,the performance of the operating system,the network connection and configuration.On the premise of guaranteeing the load balance,the cloud computer platform needs to efficiently call all kinds of hardware and software resources,rationally configure the access platform nodes,and improve the quality of the network.Cloud computing task scheduling is the core technology and research focus of cloud computing.How to allocate and schedule tasks and virtual machines is not only related to the quality of cloud services,but also to the operation cost and operation quality of the system.After introducing the background and the related features of cloud computing,this paper expounds the basic concepts and main features of task scheduling and resource load balancing in the cloud computing environment,and proposes a task scheduling strategy to reduce task scheduling time and achieve the goal of negative load balancing.A new hybrid algorithm based on sharing mechanism and swarm intelligence optimization algorithm is proposed to solve the task scheduling problem in cloud computing,so that it can adapt to the cloud computing environment better.The main contents are as follows:First of all,it studies the model of cloud computing and the popular cloud computing platform,and studies the technology of virtualization,distributed storage and programming.It provides a theoretical basis for efficient task scheduling in cloud environment.Then,the principle of ant colony algorithm,genetic algorithm and colony algorithm and the application of task scheduling in cloud environment are studied,and the advantages and disadvantages of these three algorithms are deeply analyzed.After in-depth research,a new hybrid algorithm based on sharing mechanism and swarm intelligence optimization algorithm is proposed to solve the task scheduling problem in cloud computing.The virtual machine scheduling is coded as bees,ants and genetic individuals.Then,the artificial bee colony algorithm(ABC),ant colony algorithm(ACO)and genetic algorithm(GA)are used to find the optimal solution in their neighbourhood respectively.Finally,through a sharing mechanism,the three algorithms are regularly exchanged and the best solution is used as the current optimal solution for the next iteration.In order to accelerate the convergence of the algorithm and improve the convergence accuracy.Finally,the simulation experiment is carried out in the CloudSim cloud computing simulation software,and the emphasis is made on the comparison and analysis of the completion time,load balance,cost cost and hardware configuration of the task.The experimental results show that the hybrid algorithm has more advantages in the total time of task scheduling,load balance and cost cost than the other three algorithms,and can improve the performance of the whole cloud computing system.