Research on key technology of elastic scheduling of heterogeneous cloud resources based on quantitative computing methods

Heterogeneous cloud infrastructures in cloud computing resource provisioning can improve the fault tolerance of cloud computing environments, but they also bring about difficulties that bring about cloud computing resource allocation.In order to enhance the efficiency of heterogeneous resource scheduling and allocation, this paper proposes a heterogeneous cloud resource scheduling algorithm based on the Improved Competitive Particle Swarm Algorithm (ICSO), which utilizes the chaos optimization strategy to initialize the particle swarm, and introduces Gaussian variants to update the victory particle positions to improve the diversity of the populations and to enhance the global searching ability.Simulation experiments of heterogeneous cloud resource scheduling are set up to explore the optimization effect of heterogeneous cloud resource scheduling of ICSO algorithm.Comparing the CSO algorithm and the ACO algorithm, the ICSO algorithm in this paper has a lower GD value and obtains a larger HV value in all 15 experimental data, and is able to search for the optimal solution for heterogeneous cloud resource scheduling in about 100 generations.