Service Decoupling and Deployment Strategy for Edge Computing

Li Liying; Zhang Runze; Wei Tongquan

doi:10.7544/issn1000-1239.202220736

Journal of Computer Research and Development > 2023 > 60(5): 1073-1085. > DOI: 10.7544/issn1000-1239.202220736

Li Liying, Zhang Runze, Wei Tongquan. Service Decoupling and Deployment Strategy for Edge Computing[J]. Journal of Computer Research and Development, 2023, 60(5): 1073-1085. DOI: 10.7544/issn1000-1239.202220736

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Service Decoupling and Deployment Strategy for Edge Computing

1.
School of Computer Science and Technology, East China Normal University, Shanghai 200062
2.
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094

Funds: This work was supported by the General Program of the National Natural Science Foundation of China (62272169), the Shanghai Municipal Science and Technology Major Project (2021SHZDZX), and the Project of Shanghai Trusted Industry Internet Software Collaborative Innovation Center.

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Author Bio:
Li Liying: born in 1995. PhD, lecturer. Her main research interests include Internet of things, mobile edge computing, and data analysis

Zhang Runze: born in 1997. master. His main research interests include mobile edge computing and cloud computing

Wei Tongquan: born in 1973. PhD, associate professor. His main research interests include Internet of things, mobile edge computing, and cloud computing
Received Date: August 21, 2022
Revised Date: March 29, 2023
Available Online: April 09, 2023

Graphical Abstract

Abstract

Abstract

In the era of the Internet of everything, the huge transmission delays between massive devices and data, clouds and devices have brought multiple challenges to developing applications, processing data, and ultimately improving the quality of service(QoS). As a result, edge computing architectures that significantly reduce the amount of data transferred to cloud servers and the response time of service requests by deploying computing power near end devices have emerged. However, load balancing, security, and mobility of edge devices are still the key points that affect the quality of service of edge computing architectures. In order to solve the above problems, we propose a two-stage QoS optimization scheme to solve the service deployment problem under the mobile edge computing architecture. In the first stage, we consider the decoupling of services and the load balancing of edge servers, model the problem of service deployment, propose a real-time decoupling scheme for centralized services, and design a static deployment strategy; In the second stage, we consider the mobility of edge devices, design a dynamic deployment strategy for device mobility-aware services, and optimize the quality of service under the mobile edge computing architecture. The experimental results on two datasets show that the static deployment strategy proposed in this paper can reduce the response time of service requests by 36%, and the dynamic deployment strategy can further reduce the service response time by 13%.
- edge computing,
- quality of service(QoS),
- response time,
- service decoupling,
- service deployment

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References (31)

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