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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.10641 |
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| _version_ | 1866913320785674240 |
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| author | Haag, Valentin Kiessler, Maximilian Pittl, Benedikt Schikuta, Erich |
| author_facet | Haag, Valentin Kiessler, Maximilian Pittl, Benedikt Schikuta, Erich |
| contents | Cloud resources have become increasingly important, with many businesses using cloud solutions to supplement or outright replace their existing IT infrastructure. However, as there is a plethora of providers with varying products, services, and markets, it has become increasingly more challenging to keep track of the best solutions for each application. Cloud service intermediaries aim to alleviate this problem by offering services that help users meet their requirements.
This paper aims to lay the groundwork for developing a cloud portfolio management platform and its business model, defined via a business model canvas. Furthermore, a prototype of a platform is developed offering a cloud portfolio optimization service, using two algorithms developed in previous research to create suitable and well-utilized allocations for a customer's applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_10641 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Cloud Resources Portfolio Optimization Business Model -- From Theory to Practice Haag, Valentin Kiessler, Maximilian Pittl, Benedikt Schikuta, Erich Distributed, Parallel, and Cluster Computing Multiagent Systems 91-08 J.1; H.1.m Cloud resources have become increasingly important, with many businesses using cloud solutions to supplement or outright replace their existing IT infrastructure. However, as there is a plethora of providers with varying products, services, and markets, it has become increasingly more challenging to keep track of the best solutions for each application. Cloud service intermediaries aim to alleviate this problem by offering services that help users meet their requirements. This paper aims to lay the groundwork for developing a cloud portfolio management platform and its business model, defined via a business model canvas. Furthermore, a prototype of a platform is developed offering a cloud portfolio optimization service, using two algorithms developed in previous research to create suitable and well-utilized allocations for a customer's applications. |
| title | A Cloud Resources Portfolio Optimization Business Model -- From Theory to Practice |
| topic | Distributed, Parallel, and Cluster Computing Multiagent Systems 91-08 J.1; H.1.m |
| url | https://arxiv.org/abs/2404.10641 |