Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 295-299.

• Network & Communication • Previous Articles     Next Articles

Cloud Resource Scheduling Algorithm Based on Game Theory

XU Fei1,2, WANG Shao-chang1, YANG Wei-xia1   

  1. School of Computer Science and Engineering,Xi'an Technological University,Xi'an710021,China1;
    School of Marine Engineering,Northwestern Polytechnical University,Xi'an 710072,China2
  • Online:2019-06-14 Published:2019-07-02

Abstract: In a large data center in a cloud environment,the number of virtual machines and the load of virtual machines change frequently with the needs of users and applications.The virtual machines need to make dynamic resource adjustments to remove hotspot resources in the system in time and implement load banlancing for the entire system.Now through theoretical research on cloud resource allocation,we have obtained such applications as First-Fit greedy algorithm and Round Robin polling algorithm that can be applied to some cloud systems to solve problems in a short time,but they have the problems of resource utilization and load.Therefore,this paper proposed a fuzzy-future-memory tradeoff (GMO) cloud resource scheduling algorithm based on game theory.The algorithm breaks a fixed number of resource allocation bottlenecks,takes QoS into consideration,and solves problems of resource utilization and resource allocation fairness.Simulation results show that FUTG algorithm can significantly improve the effectiveness of dynamic resource scheduling and the efficiency of resource usage under dynamic load.

Key words: Cloud resources dispatch, QoS, Game theory, FUTG, Dynamic load

CLC Number: 

  • TP18
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