Task Scheduling Algorithm Based on Bidirectional Optimization Genetic Algorithm in Cloud Computing Environment

the task scheduling of cloud computing was studied, from the point of reducing the completion time and execution cost of tasks, a cloud computing task scheduling algorithm was proposed. Firstly, establish the models of completion time and execution cost for cloud computing tasks, and carry out the weight setting for the two optimization goals time and cost; and then, propose a Bidirectional Optimization Genetic Algorithm (BOGA), use the normal distribution function and optimal individuals to preserve the design selection, crossover and mutation operators and solve the optimal scheme for task scheduling. Perform the simulation of BOGA algorithm in CloudSim, the results show that the proposed scheduling algorithm can achieve the bidirectional optimization for the completion time and execution cost of tasks and is a feasible scheduling algorithm in cloud computing.