Scheduling Model for Cloud Computing Based on Multi-Objective Genetic Algorithm

Cloud computing is an emerging high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. To improve the overall performance of cloud computing, with the deadline constraint, a task scheduling model is established for reducing the system power consumption of cloud computing and improving the profit of service providers. For the scheduling model, a solving method based on multi-objective genetic algorithm (MO-GA) is designed and the research is focused on encoding rules, crossover operators, selection operators and the method of sorting Pareto solutions. Based on open source cloud computing simulation platform CloudSim, compared to existing scheduling algorithms, the results show that the proposed algorithm can obtain a better solution, and it provides a balance for the performance of multiple objects