Journal of Xidian University ›› 2021, Vol. 48 ›› Issue (6): 16-22.doi: 10.19665/j.issn1001-2400.2021.06.003

• Special Issue:Key Technology of Architecture and Software for Intelligent Embedded Systems • Previous Articles     Next Articles

Multi-node cooperative game load balancing strategy in the Kubernetes cluster

LI Huadong1,2,3(),ZHANG Xueliang2,3(),WANG Xiaolei2,3(),LIU Hui1(),WANG Pengcheng1(),DU Junzhao1()   

  1. 1. School of Computer Science and Technology,Xidian University,Xi’an 710071,China
    2. CETC Key Laboratory of Aerospace Information Applications,Shijiazhuang 050081,China
    3. The 54th Research Institute of CETC,Shijiazhuang 050081,China
  • Received:2021-09-02 Online:2021-12-20 Published:2022-02-24
  • Contact: Hui LIU E-mail:r1v3n@foxmail.com;18332186667@163.com;931104914@qq.com;liuhui@xidian.edu.cn;wpc-0806@163.com;dujz@xidian.edu.cn

Abstract:

Kubernetes has the potential to become a new generation of hyper-converged architecture,but there are still some problems in the research on cluster resource load balancing:on the one hand,most of the existing scheduling algorithms are static scheduling algorithms,and the dynamics of cluster resources in actual use are not considered; on the other hand,the existing research on solving cluster resource load balancing only optimizes the CPU and memory resources in the cluster,but cannot give a complete resource profile of the cluster,with the algorithm lacking comprehensiveness.In this paper,we introduce the MBCGT,a multi-resource load balancing algorithm based on the cooperative game theory for Kubernetes cluster scheduling,and proposes the index of cluster resource load balance to optimize scheduling and reduce the fragmentation of cluster resources.First,we use real-time monitoring to obtain the actual resource usage of service requests to achieve dynamic service scheduling.Second,we consider the load balance among the four resources of cluster CPU,memory,network bandwidth and disk IO,establish a cooperative game model between physical nodes to ensure the lower bound of the MBCGT algorithm when facing different resource requests of various applications,and solve the cluster Resource fragmentation phenomenon.Finally,the algorithm is tested in a real Kubernetes cluster.The results show that the MBCGT algorithm reduces the fragmentation of cluster resources,and that the average load balance of each node in the cluster can be increased by 8.40%.

Key words: cloud computing, Kubernetes cluster, cooperative game theory, multi-resource load balancing

CLC Number: 

  • TP306