An Improvement of Task Scheduling Algorithms for Green Cloud Computing


The energy consumption generated by servers in task scheduling is an important part of the dynamic energy consumption of cloud computing systems. Saving energy and improving energy efficiency are important foundations for realizing green cloud computing systems. Under green cloud computing, this paper aims to reduce energy consumption and shorten task execution time. This paper combines genetic algorithm and ant colony algorithm to propose a dynamic fusion task-scheduling algorithm. Thereby reducing the energy consumption of cloud computing data centers and computing centers. The simulation results show that the proposed task scheduling algorithm can significantly reduce the time and total energy consumption of cloud computing system tasks.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL