Energy-efficient Cloud Task Scheduling Research based on Dynamic Genetic Algorithm

The rapid development of cloud computing has led to the establishment of large- scale data centers. Such data centers consume enormous amounts of electric energy,resulting in high operating cost and carbon dioxide emissions. With the aid of traditional genetic algorithm,the paper presents a new multi- objective dynamic scheduling algorithm,which considers cloud environment dynamics and reduces total execution time and power consumption. The new algorithm assigns the jobs to the resources according to the job length and resources capacities. After that,the paper evaluates this algorithm with some famous cloud scheduling algorithm,and the experiments show the efficiency of the proposed approach in terms of execution time,power consumption in cloud environment.