Application of cloud computing technology in enterprise resource management

Research Article
Open access

Application of cloud computing technology in enterprise resource management

Ziqi Wang 1*
  • 1 Stony Brook University    
  • *corresponding author ziqi.wang.3@stonybrook.edu
Published on 7 February 2024 | https://doi.org/10.54254/2755-2721/38/20230552
ACE Vol.38
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-301-2
ISBN (Online): 978-1-83558-302-9

Abstract

The progress of intelligent manufacturing has made enterprise resource planning (ERP) an essential core technology in the field of intelligent manufacturing. In the process of technology development, enterprises have been looking for a more optimized ERP architecture, and cloud-based ERP is one of the practical and efficient solutions. However, for the application of cloud computing in ERP, the current summary analysis based on this field is not comprehensive enough. In this paper, a comprehensive examination of the real-world implementation of cloud computing in ERP is conducted. It delves into the practical utilization and transformation of service-oriented architecture (SOA) and Model View Controller (MVC) within the context of ERP, while also providing an overview of the merits and drawbacks of SOA technology. At the same time, it summarizes the concept of layering and the practical application of cloud computing in different layers for human resource management system of enterprises. In addition, this paper summarizes the practical applications and development prospects of cloud computing in enterprise resource management, such as resource sharing and virtualization. Finally, the paper summarizes the full text, and puts forward a summary and prospect of the combination and future development of cloud computing and enterprise resource management.

Keywords:

cloud computing, enterprise resource management, SOA, MVC, human resource management

Wang,Z. (2024). Application of cloud computing technology in enterprise resource management. Applied and Computational Engineering,38,192-199.
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References

[1]. Wen Y. Research and Implementation of Intelligent ERP Platform for SMEs Based on Cloud Computing. IOP conference series. Materials Science and Engineering. 2019;646(1):12014–21.

[2]. Lv T, Zhang J, Chen Y. Research of ERP Platform based on Cloud Computing. IOP conference series. Materials Science and Engineering. 2018;394(4):42004

[3]. Wang XL, Wang L, Bi Z, Li YY, Xu Y. Cloud computing in human resource management (HRM) system for small and medium enterprises (SMEs). International journal of advanced manufacturing technology. 2016;84(1-4):485-496.

[4]. Overbeek S, Klievink B, Janssen M. A Flexible, Event-Driven, Service-Oriented Architecture for Orchestrating Service Delivery. IEEE intelligent systems. 2009;24(5):31–41.

[5]. Lombardi F, Di Pietro R. Secure virtualization for cloud computing. Journal of network and computer applications. 2011;34(4):1113–1122.

[6]. Mauch V, Kunze M, Hillenbrand M. High performance cloud computing. Future generation computer systems. 2013;29(6):1408–1416.

[7]. Benlian A, Hess T. Opportunities and risks of software-as-a-service: Findings from a survey of IT executives. Decision Support Systems. 2011;52(1):232–246.

[8]. Porambage P, Okwuibe J, Liyanage M, Ylianttila M, Taleb T. Survey on Multi-Access Edge Computing for Internet of Things Realization. IEEE Communications surveys and tutorials. 2018;20(4):2961-2991.

[9]. Heilig L, Lalla-Ruiz E, Vo S. A cloud brokerage approach for solving the resource management problem in multi-cloud environments. Computers & industrial engineering. 2016;95:16-26.

[10]. Larrucea X, Santamaria I, Colomo-Palacios R, Ebert C. Microservices. IEEE software. 2018;35(3):96–100.

Cite this article

Wang,Z. (2024). Application of cloud computing technology in enterprise resource management. Applied and Computational Engineering,38,192-199.

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

ISBN：978-1-83558-301-2(Print) / 978-1-83558-302-9(Online)
Editor：Mustafa İSTANBULLU
Conference website: https://2023.confmla.org/
Conference date: 18 October 2023
Series: Applied and Computational Engineering
Volume number: Vol.38
ISSN：2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
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References

[1]. Wen Y. Research and Implementation of Intelligent ERP Platform for SMEs Based on Cloud Computing. IOP conference series. Materials Science and Engineering. 2019;646(1):12014–21.

[2]. Lv T, Zhang J, Chen Y. Research of ERP Platform based on Cloud Computing. IOP conference series. Materials Science and Engineering. 2018;394(4):42004

[3]. Wang XL, Wang L, Bi Z, Li YY, Xu Y. Cloud computing in human resource management (HRM) system for small and medium enterprises (SMEs). International journal of advanced manufacturing technology. 2016;84(1-4):485-496.

[4]. Overbeek S, Klievink B, Janssen M. A Flexible, Event-Driven, Service-Oriented Architecture for Orchestrating Service Delivery. IEEE intelligent systems. 2009;24(5):31–41.

[5]. Lombardi F, Di Pietro R. Secure virtualization for cloud computing. Journal of network and computer applications. 2011;34(4):1113–1122.

[6]. Mauch V, Kunze M, Hillenbrand M. High performance cloud computing. Future generation computer systems. 2013;29(6):1408–1416.

[7]. Benlian A, Hess T. Opportunities and risks of software-as-a-service: Findings from a survey of IT executives. Decision Support Systems. 2011;52(1):232–246.

[8]. Porambage P, Okwuibe J, Liyanage M, Ylianttila M, Taleb T. Survey on Multi-Access Edge Computing for Internet of Things Realization. IEEE Communications surveys and tutorials. 2018;20(4):2961-2991.

[9]. Heilig L, Lalla-Ruiz E, Vo S. A cloud brokerage approach for solving the resource management problem in multi-cloud environments. Computers & industrial engineering. 2016;95:16-26.

[10]. Larrucea X, Santamaria I, Colomo-Palacios R, Ebert C. Microservices. IEEE software. 2018;35(3):96–100.

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