A task scheduling algorithm considering game theory designed for energy management in cloud computing - Yang, Jiachen; Jiang, Bin; Lv, Zhihan; Choo, Kim-Kwang Raymond (Future generation computer systems, 2020)
With the increasing popularity of cloud computing products, task scheduling problem has become a hot research topic in this field. The task scheduling problem of cloud computing system is more complex than the traditional distributed system. Based on the analysis of cloud computing in related literature, we established a simplified model for task scheduling system in cloud computing.Different from the previous research of cloud computing task scheduling algorithm, the simplified model in this paper is based on game theory as a mathematical tool. Based on game theory, the task scheduling algorithm considering the reliability of the balanced task is proposed. Based on the balanced scheduling algorithm, the task scheduling model for computing nodes is proposed. In the cooperative game model, game strategy is used for the task in the calculation of rate allocation strategy on the node. Through analysis of experimental results, it is shown that the proposed algorithm has better optimization effect. •In this paper, we propose a task scheduling algorithm considering game theory designed for energy management in cloud computing.•First of all, the game theory can better coordinate the distribution of task and the distribution of energy.•The task scheduling model for computing nodes by establishing mathematical model is proposed to deal with big data.•In addition, experimental verification in this paper is both in equilibrium state and balanced calculation ability.•In a word, task scheduling algorithm considering game theory is designed for big data in cloud computing. And experiments show that the algorithm can improve the energy management in cloud computing.