A multi-resource scheduling scheme of Kubernetes for IIoT

doi:10.23919/JSEE.2022.000063

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (3): 683-692.doi: 10.23919/JSEE.2022.000063

收稿日期:2021-01-26 出版日期:2022-06-18 发布日期:2022-06-24

A multi-resource scheduling scheme of Kubernetes for IIoT

Lin ZHU¹(), Junjiang LI¹(), Zijie LIU¹(), Dengyin ZHANG^1,^2,*()

¹ Jiangsu Key Laboratory of Broadband Wireless Communication and Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
² School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Received:2021-01-26 Online:2022-06-18 Published:2022-06-24
Contact: Dengyin ZHANG E-mail:zhulin_xzz@163.com;admin@run-linux.com;439450110@qq.com;zhangdy@njupt.edu.cn
About author:|ZHU Lin was born in 1996. She received her B.S. degree from Nantong University, Nantong, China, in 2014. She is currently pursuing her M.S. degree in logistics engineering with Nanjing University of Posts and Telecommunications, Nanjing, China. Her current research interests include cloud computing and distributed systems. E-mail: zhulin_xzz@163.com||LI Junjiang was born in 1996. He received his B.S. degree from Tongda College of Nanjing University of Posts and Telecommunications, Yangzhou, China, in 2014. He is currently pursuing his M.S. degree in logistics engineering with Nanjing University of Posts and Telecommunications, Nanjing, China. His current research interests include cloud computing, container orchestration systems, and distributed systems. E-mail: admin@run-linux.com||LIU Zijie was born in 1996. He received his B.S. degree from Nanjing Institute of Technology, Nanjing, China, in 2014. He is currently pursuing his Ph.D. degree in information network with Nanjing University of Posts and Telecommunications, Nanjing, China. His current research interests include cloud computing and distributed systems. E-mail: 439450110@qq.com||ZHANG Dengyin was born in 1964. He received his B.S., M.S. and Ph.D. degrees in Nanjing University of Posts and Telecommunications, Nanjing, China, in 1986, 1989 and 2004 respectively. He is currently a professor of the School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China. He was in Digital Media Lab at Umea University in Sweden as a visiting scholar from 2007 to 2008. His research interests include signal and information processing, networking technique, and information security. E-mail: zhangdy@njupt.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (61872423), the Industry Prospective Primary Research & Development Plan of Jiangsu Province (BE2017111), and the Scientific Research Foundation of the Higher Education Institutions of Jiangsu Province (19KJA180006).

摘要/Abstract

Abstract:

With the rapid development of data applications in the scene of Industrial Internet of Things (IIoT), how to schedule resources in IIoT environment has become an urgent problem to be solved. Due to benefit of its strong scalability and compatibility, Kubernetes has been applied to resource scheduling in IIoT scenarios. However, the limited types of resources, the default scheduling scoring strategy, and the lack of delay control module limit its resource scheduling performance. To address these problems, this paper proposes a multi-resource scheduling (MRS) scheme of Kubernetes for IIoT. The MRS scheme dynamically balances resource utilization by taking both requirements of tasks and the current system state into consideration. Furthermore, the experiments demonstrate the effectiveness of the MRS scheme in terms of delay control and resource utilization.

Key words: Industrial Internet of Things (IIoT), Kubernetes, resource scheduling, time delay

. [J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 683-692.

Lin ZHU, Junjiang LI, Zijie LIU, Dengyin ZHANG. A multi-resource scheduling scheme of Kubernetes for IIoT[J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 683-692.

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参考文献 22

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Equipment	Configuration
CPU/cores	20
Memory/MB	32768
Band width/Gbps	10
Storage/GB	1000

Scheduling method	Cluster resource imbalance		Reasonable rate of scheduling
Scheduling method	2000 pods	10000 pods	2000 pods	10000 pods
DRS	0.22	0.42	1	0.92
Ant colony algorithm ^[22]	0.21	0.34	1	1
MRS	0.21	0.35	1	1

A multi-resource scheduling scheme of Kubernetes for IIoT

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