| 英文标题 | Task arrival awareness scheduler in large-scale server clusters |
| 作者英文名 | Cai Wenwei, Zhu Jiaxian, Zhang Huibing |
| 机构英文名 | 1.School of Computer Science & Software,School of Big Data,Zhaoqing University,Zhaoqing Guangdong 526061,China;2.Guangxi Key Laboratory of Trusted Software,Guilin University of Electronic Technology,Guilin Guangxi 541004,China |
| 英文摘要 | The control cost and performance difference of various servers in the heterogeneous cloud data center will affect to the operation and maintenance management cost and QoS game balance. Since the task arrival rate is time-sensitive, this paper presented a large-scale task scheduling with task arrival rate awareness. Using the task arrival rate and the current state of the server in the cluster, based on saving server operation costs and load balancing of each server in task scheduling, the model could optimize the mean response time and system throughput of the heterogeneous cloud data center. By analyzing of the experimental results, it verifies that the credibility of the cluster server control model in task scheduling is at least at a confidence level of 95%. By comparing with the strategy of SRPT and RabbitMQ, the result verifies the validity and feasibility of the model. |
| 英文关键词 | heterogeneous cloud data center; large scale scheduling problem; load balancing; multi-server controller |