Reducing Idleness in Financial Cloud Services via Multi-objective Evolutionary Reinforcement Learning based Load Balancer.

Peng Yang1; Laoming Zhang2; Haifeng Liu3; Guiying Li4

2023-11-21

10.1007/s11432-023-3895-3

SCIENCE CHINA Information Sciences   影响因子和分区

1674-733X

1869-1919

In recent years, various companies have started to shift their data services from traditional data centers to the cloud. One of the major motivations is to save on operational costs with the aid of cloud elasticity. This paper discusses an emerging need from financial services to reduce the incidence of idle servers retaining very few user connections, without disconnecting them from the server side. This paper considers this need as a bi-objective online load balancing problem. A neural network based scalable policy is designed to route user requests to varied numbers of servers for the required elasticity. An evolutionary multi-objective training framework is proposed to optimize the weights of the policy. Not only is the new objective of idleness reduced by over 130% more than traditional industrial solutions, but the original load balancing objective itself is also slightly improved. Extensive simulations with both synthetic and real-world data help reveal the detailed applicability of the proposed method to the emergent problem of reducing idleness in financial services.

cloud computing evolutionary multi-objective optimization evolutionary reinforcement learning load balance

SCI ; EI

英语

第一 ; 通讯

2-s2.0-85183769098

人工提交

1.Room 316, Business School, Southern University of Science and Technology , shenzhen Guangdong China 518055
2.Room 619B, College of Engineering , Shenzhen Guangdong China 518055
3.OPPO , shenzhen China 518052
4.Room 646, College of Engineering , shenzhen Guangdong China 518055

Peng Yang,Laoming Zhang,Haifeng Liu,et al. Reducing Idleness in Financial Cloud Services via Multi-objective Evolutionary Reinforcement Learning based Load Balancer.[J]. SCIENCE CHINA Information Sciences,2023,67(2).

Peng Yang,Laoming Zhang,Haifeng Liu,&Guiying Li.(2023).Reducing Idleness in Financial Cloud Services via Multi-objective Evolutionary Reinforcement Learning based Load Balancer..SCIENCE CHINA Information Sciences,67(2).

Peng Yang,et al."Reducing Idleness in Financial Cloud Services via Multi-objective Evolutionary Reinforcement Learning based Load Balancer.".SCIENCE CHINA Information Sciences 67.2(2023).