Focusing on the problem of high efficiency and effectiveness resource scheduling in cloud computing environments

the model of cloud resource scheduling is systematically analyzed in theory at first

the application preferences and the user utility of multi-dimensional QoS is quantified

and the objective function of multi-dimensional QoS is given at last.Combining with the immune clonal algorithm of rapid multi-objective optimization

a heuristic cloud resource scheduling algorithm with application preference is proposed.The non-dominated antibodies are proportionally immune cloned according to their preference priority

which are defined by their cloud application preferences.It is beneficial to enhance the forecasting accuracy of the immune gene manipulation

and to increase the speed of finding the optimal solution based on the application preference.Experimental results conclusively demonstrate the efficiency and effectiveness of the improve system availability

load balancing deviation and valid time brought by the proposed algorithm in cloud computing environments.