Hybrid Cloud Strategies for Enterprise Fulfilment Applications: A Performance and Scalability Perspective
DOI:
https://doi.org/10.54741/asejar.1.2.6Keywords:
hybrid, cloud strategies, edge computingAbstract
This paper explores three prominent hybrid cloud strategies—Cloud Bursting, Multi-Cloud, and Hybrid Multi-Cloud with Edge Computing—specifically in the context of enterprise fulfilment applications such as order data stores and inventory management systems. These strategies provide scalability, cost efficiency, and flexibility, addressing the performance and operational challenges of modern enterprises. The paper analyzes the benefits and challenges of each strategy in terms of scalability, cost efficiency, latency, and security. A comparative analysis reveals that Cloud Bursting is optimal for handling seasonal demand surges, multi-cloud offers high reliability for global operations, and Hybrid Multi-Cloud with Edge Computing provides superior performance for real-time, low-latency applications. The paper concludes by highlighting the need for further research on integration, security innovations, cost optimization, and advancements in edge computing to address the challenges in hybrid cloud strategies for enterprise applications.
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References
Jatoth, Chandrashekar, et al. (2019). SELCLOUD: A hybrid multi-criteria decision-making model for selection of cloud services. Soft Computing, 23, 4701-4715.
Sohaib, Osama, et al. (2019). Cloud computing model selection for e-commerce enterprises using a new 2-tuple fuzzy linguistic decision-making method. Computers & Industrial Engineering, 132, 47-58.
Ren, Lei, et al. (2017). Cloud manufacturing: key characteristics and applications. International Journal of Computer Integrated Manufacturing, 30(6), 501-515.
Nieuwenhuis, Lambert JM, Michel L. Ehrenhard, & Lars Prause. (2018). The shift to Cloud Computing: The impact of disruptive technology on the enterprise software business ecosystem. Technological Forecasting and Social Change, 129, 308-313.
Sturgeon, Timothy J. (2021). Upgrading strategies for the digital economy. Global Strategy Journal, 11(1), 34-57.
Acuña-Carvajal, Felipe, et al. (2019). An integrated method to plan, structure and validate a business strategy using fuzzy DEMATEL and the balanced scorecard. Expert Systems with Applications, 122, 351-368.
Wang, Xi Vincent, et al. (2017). Ubiquitous manufacturing system based on Cloud: A robotics application." Robotics and Computer-Integrated Manufacturing, 45, 116-125.
Khalil, Sabine. (2019). Adopting the cloud: how it affects firm strategy. Journal of Business Strategy, 40(4), 28-35.
Leung, K. H., et al. (2018). A B2C e-commerce intelligent system for re-engineering the e-order fulfilment process. Expert Systems with Applications, 91, 386-401.
Raghunath, Vedaprada, Mohan Kunkulagunta, & Geeta Sandeep Nadella. (2021). Machine learning models for optimizing SAP-based data processing in cloud environments. International Journal of Sustainable Development in Computing Science, 3(3).
Ali, Omar, et al. (2018). Cloud computing-enabled healthcare opportunities, issues, and applications: A systematic review. International Journal of Information Management, 43, 146-158.
Adamson, Göran, et al. (2017). Cloud manufacturing–a critical review of recent development and future trends. International Journal of Computer Integrated Manufacturing, 30(4-5), 347-380.
Sunyaev, Ali, & Ali Sunyaev. (2020). Cloud computing. Internet Computing: Principles of Distributed Systems and Emerging Internet-Based Technologies, 195-236.
Buldeo Rai, Heleen, et al. (2019). Logistics outsourcing in omnichannel retail: State of practice and service recommendations. International Journal of Physical Distribution & Logistics Management, 49(3), 267-286.
Taylor, Daniel, et al. (2019). Omnichannel fulfillment strategies: Defining the concept and building an agenda for future inquiry. The International Journal of Logistics Management, 30(3), 863-891.
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Copyright (c) 2022 Anil Kumar Anusuru
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Research Articles in 'Applied Science and Engineering Journal for Advanced Research' are Open Access articles published under the Creative Commons CC BY License Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/. This license allows you to share – copy and redistribute the material in any medium or format. Adapt – remix, transform, and build upon the material for any purpose, even commercially.